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Published online by Cambridge University Press:  05 July 2014

K. Selçuk Candan
Affiliation:
Arizona State University
Maria Luisa Sapino
Affiliation:
Università degli Studi di Torino, Italy
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Print publication year: 2010

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References

Swarup, Acharya, Viswanath, Poosala, and Sridhar, Ramaswamy. Selectivity estimation in spatial databases. In SIGMOD '99: Proceedings of the 1999 ACM SIGMOD International Conference on Management of Data, pages 13-24, 1999.
S., Adali and M. L., Sapino. An activity based data model for desktop querying. In Proceedings of the Semantic Desktop Workshop, 2005.
S., Adali, M. L., Sapino, and V. S., Subrahmanian. A multimedia presentation algebra. SIGMOD Rec., 28(2):121–132, 1999.Google Scholar
S., Adali, B., Bouqata, A., Marcus, F., Spear, and B., Szymanski. A day in the life of a metamorphic petrologist. In Proc. ICDE Workshop on Semantic Web and Databases, 2006.
Sibel Adali, K.Selçuk, Candan, Su-Shing, Chen, Kutluhan, Erol, and V. S., Subrah-manian. The advanced video information system: data structures and query processing. Multimedia Syst., 4(4):172–186, 1996.Google Scholar
Sibel, Adali, Corey, Bufi, and Maria Luisa, Sapino. Ranked relations: Query languages and query processing methods for multimedia. Multimedia Tools Appl., 24(3):197–214, 2004.Google Scholar
Sibel, Adali, Maria Luisa, Sapino, and Brandeis, Marshall. A rank algebra to support multimedia mining applications. In MDM '07: Proceedings of the 8th International Workshop on Multimedia Data Mining, pages 1-9, 2007.
R., Adams and L., Bischof. Seeded region growing. IEEE Trans. Pattern Anal. Mach. Intell., 16(6):641–647, 1994.Google Scholar
Charu C., Aggarwal, Joel L., Wolf, Kun-Lung, Wu, and Philip S., Yu. Horting hatches an egg: a new graph-theoretic approach to collaborative filtering. In KDD '99: Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 201-212, 1999.
R., Agrawal, A., Borgida, and H. V., Jagadish. Efficient management of transitive relationships in large data and knowledge bases. In SIGMOD '89: Proceedings of the 1989 ACM SIGMOD International Conference on Management of Data, pages 253-262, 1989.
A. V., Aho and M. J., Corasick. Efficient string matching: An aid to bibliographic search. Communications of the ACM, 18(6):333–340, June 1975.Google Scholar
H., Akaike. A new look at the statistical model identification. IEEE Trans. Automat. Contr. 19(6):716-723, 1974.Google Scholar
D., Akca. Generalized Procrustes analysis and its applications in photogrammetry. In Internal Colloquium at Photogrammetry and Remote Sensing Group oflGP — ETH Zurich, Zurich, Switzerland, 2003.
James F., Allen. Maintaining knowledge about temporal intervals. Commun. ACM, 26(11):832–843, 1983.Google Scholar
James F., Allen. Towards a general theory of action and time. Artif. Intell., 23(2): 123-154, 1984.Google Scholar
D., Aloise, A., Deshpande, P., Hansen, and P., Popat. NP-hardness of Euclidean sum-of- squares clustering. Cahiers du GERAD, G-2008-33, 2008.
Rajeev, Alur and David L., Dill. A theory of timed automata. Theor. Comput. Sci., 126:183–235, 1994.Google Scholar
A., Amir, G. M., Landau, M., Lewenstein, and N., Lewenstein. Eficient special cases of pattern matching with swaps. Inf. Proc. Lett., 68(3):125–132, 1998.Google Scholar
Yali, Amit and Donald, Geman. Shape quantization and recognition with randomized trees. Neural Comput., 9(7):1545–1588, 1997.Google Scholar
D. P., Anderson. Techniques for reducing pen plotting time. ACM Trans. Graph., 2(3):197–212, 1983a.Google Scholar
John R., Anderson. A spreading activation theory of memory. J. Verbal Learn. Verbal Behav., 22:261–295, 1983b.Google Scholar
Alexandr, Andoni and Piotr, Indyk. Efficient algorithms for substring near neighbor problem. In SODA '06: Proceedings of the Seventeenth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 1203-1212, 2006a.
Alexandr, Andoni and Piotr, Indyk. Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions. In FOCS '06: Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science, pages 459-468, 2006b.
Alexandr, Andoni and Piotr, Indyk. Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions. Commun. ACM, 51(1):117–122, 2008.Google Scholar
Christophe, Andrieu, Nando, de Freitas, Arnaud, Doucet, and Michael I., Jordan. An introduction to mcmc for machine learning. Mach. Learn., 50(1-2):5-43, 2003.Google Scholar
Benjamin, Arai, Gautam, Das, Dimitrios, Gunopulos, and Nick, Koudas. Anytime measures for top-k algorithms. In VLDB, pages 914-925, 2007.
Hiroshi, Arisawa, Takashi, Tomii, and Kiril, Salev. Design of multimedia database and a query language for video image data. In ICMCS, 1996.
Sunil, Arya, David M., Mount, Nathan S., Netanyahu, Ruth, Silverman, and Angela Y., Wu. An optimal algorithm for approximate nearest neighbor searching in fixed dimensions. In ACM-SIAM Symposium on Discrete Algorithms, pages 573–582, 1994.
Sunil, Arya, David M., Mount, Nathan S., Netanyahu, Ruth, Silverman, and Angela Y., Wu. An optimal algorithm for approximate nearest neighbor searching ixed dimensions. J. ACM, 45(6):891–923, 1998.Google Scholar
Y. Alp, Aslandogan, Chuck, Thier, Clement T., Yu, Chengwen, Liu, and Krishnakumar R., Nair. Design, implementation and evaluation of score (a system for content based retrieval of pictures). In ICDE '95: Proceedings of the Eleventh International Conference on Data Engineering, pages 280–287, Washington, DC, USA, 1995. IEEE Computer Society.
Bengt, Aspvall and Yossi, Shiloach. A polynomial time algorithm for solving systems of linear inequalities with two variables per inequality. SIAM J. Comput., 9(4): 827-845, 1980.Google Scholar
M. P., Atkinson, F., Bancillon, D., De-Witt, K., Dittrich, D., Maier, and S., Zdonik. The object-oriented database system manifesto. In Proceedings of the First Deductive and Object-oriented Database Conference, pages 40–57, Kyoto, 1989.
Jeffrey R., Bach, Charles, Fuller, Amarnath, Gupta, Arun, Hampapur, Bradley, Horowitz, Rich, Humphrey, Ramesh C., Jain, and Chiao-Fe, Shu. Virage Image Search Engine: an Open Framework for Image Management, Volume 2670, pages 76-87. SPIE, 1996.
R., Baeza-Yates and G. H., Gonnet. Fast text searching for regular expressions or automaton searching on tries. J. ACM (JACM), 43(6):915–936, 1996.Google Scholar
R. A., Baeza-Yates and G. H., Gonnet. A new approach to text searching. In SIGIR '89: Proceedings of the 12th annual international ACM SIGIR conference on Research and development in information retrieval, pages 168–175, 1989.
Ricardo, Baeza-Yates and Gaston H., Gonnet. A new approach to text searching. Commun. ACM, 35(10):74–82, 1992.Google Scholar
Ricardo, Baeza-Yates and Gonzalo, Navarro. New and faster filters for multiple approximate string matching. Random Struct. Algorithms, 20(1):23–49, 2002.Google Scholar
Ricardo, Baeza-Yates and Gonzalo, Navarro. Faster approximate string matching. Algorithmica, 23:174–184, 1999.Google Scholar
Ricardo A., Baeza-Yates. A unified view to string matching algorithms. In SOFSEM '96: Proceedings of the 23rd Seminar on Current Trends in Theory and Practice of Informatics, pages 1–15, 1996.
Ricardo A., Baeza-Yates and Chris H., Perleberg. Fast and practical approximate string matching. In CPM '92: Proceedings of the Third Annual Symposium on Combinatorial Pattern Matching, pages 185–192, 1992.
Ricardo A., Baeza-Yates and Berthier A., Ribeiro-Neto. Modern Information Retrieval. ACM Press/Addison-Wesley, 1999.
Gianfranco, Balbo. Introduction to Stochastic Petri Nets, pages 84-155, 2002.
W.-T., Balke and U., Guntzer. Efficient skyline queries under weak Pareto dominance. In Proc. of the IJCAI-05 Multidisciplinary Workshop on Advances in Preference Handling (PREFERENCE), pages 1–7, 2005.
Wolf-Tilo, Balke, Ulrich, Guntzer, and Wolf, Siberski. Exploiting indifference for customization of partial order skylines. In IDEAS '06: Proceedings ofthe 10th International Database Engineering and Applications Symposium, pages 80–88, 2006.
Nevzat Hurkan, Balkir, Eser, Sükan, Gultekin, Özsoyoglu, and Z. Meral, Özsoyoglu. Visual: A graphical icon-based query language. In Stanley, Y. W. Su, editor, Proceedings of the Twelfth International Conference on Data Engineering, February 26-March 1, 1996, New Orleans, Louisiana, pages 524–533, 1996.
Nevzat Hurkan, Balkir, Gultekin, Ozsoyoglu, and Z. Meral, Ozsoyoglu. A graphical query language: Visual and its query processing. IEEE Trans. Knowl. Data Eng., 14(5):955–978, 2002.Google Scholar
L., Balmelli and A., Mojsilovic. Wavelet domain features for texture description, classification and replicability analysis. In ICIP99, pages IV:440-444, 1999.
Nilesh, Bansal, Sudipto, Guha, and Nick, Koudas. Ad-hoc aggregations of ranked lists in the presence of hierarchies. In SIGMOD Conference, pages 67–78, 2008.
A. L., Barabasi and R., Albert. Emergence of scaling in random networks. Science, 286:509–512, October 1999.Google Scholar
Chitta, Baral, Graciela, Gonzalez, and Tran Cao, Son. Design and implementation of display specification for multimedia answers. In ICDE '98: Proceedings of the Fourteenth International Conference on Data Engineering, pages 558-565. IEEE Computer Society, 1998.
Mark A., Bartsch and Gregory H., Wakefield. To catch a chorus: Using chroma-based representations for audio thumbnailing. In Proceedings of the 2001 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, pages 15–18, 2001.
Chumki, Basu, Haym, Hirsh, and William, Cohen. Recommendation as classification: using social and content-based information in recommendation. In AAAI '98/IAAI '98: Proceedings of the Fifteenth National/Tenth Conference on Artificial Intelligence/Innovative Applications of Artificial Intelligence, pages 714–720, 1998.
L. E., Baum and G. R., Sell. Growth transformations for functions on manifolds. Pacific J. Math., 27:211–227, 1968.Google Scholar
L. E., Baum and J. A., Eagon. An inequality with applications to statistical estimation for probabilistic functions of Markov processes and to a model for ecology. Bull. Am. Math. Soc., 73:360–363, 1967.Google Scholar
Leonard E., Baum, Ted, Petrie, George, Soules, and Norman, Weiss. A maximization technique occurring in the statistical analysis of probabilistic functions of markov chains. Ann. Mathemat. Statist., 41(1):164–171, 1970.Google Scholar
Herbert, Bay, Tinne, Tuytelaars, and Luc Van, Gool. Surf: Speeded up robust features. In ECCV, pages 404–417, 2006.
Rudolf, Bayer and E., McCreight. Organization and Maintenance of Large Ordered Indexes, pages 245-262, 2002.
Rudolf, Bayer and Edward M., McCreight. Organization and maintenance of large ordered indices. Acta Inform., 1:173–189, 1972.Google Scholar
Norbert, Beckmann, Hans-Peter, Kriegel, Ralf, Schneider, and Bernhard, Seeger. The r*-tree: an efficient and robust access method for points and rectangles. In Proceedings of the 1990 ACM SIGMOD International Conference on Management of Data, pages 322–331, 1990.
Serge, Belongie, Jitendra, Malik, and Jan, Puzicha. Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intellig., 24:509-522, 2002.Google Scholar
Alberto, Belussi and Christos, Faloutsos. Estimating the selectivity of spatial queries using the “correlation” fractal dimension. In VLDB '95: Proceedings of the 21th International Conference on Very Large Data Bases, pages 299–310, 1995.
Alberto, Belussi and Christos, Faloutsos. Self-spatial join selectivity estimation using fractal concepts. ACM Trans. Inf. Syst., 16(2):161–201, 1998.Google Scholar
Charles H., Bennett, Pter, Gcs, Senior Member, Ming, Li, Paul M. B., Vitnyi, and Wojciech H., Zurek. Information distance. IEEE Trans. Inform. Theory, 44:1407–1423, 1998.Google Scholar
Kristin P., Bennett and Erin J., Bredensteiner. Duality and geometry in svm classifiers. In ICML '00: Proceedings of the Seventeenth International Conference on Machine Learning, pages 57–64, 2000.
Kristin P., Bennett and Colin, Campbell. Support vector machines: hype or hallelujah?SIGKDD Explor. Newsl., 2(2):1–13, 2000.Google Scholar
J. L., Bentley. Algorithms for klee's rectangle problems. Dept. of Computer Science, Carnegie Mellon University, 1977.
Jon Louis, Bentley. Multidimensional binary search trees used for associative searching. Commun. ACM, 18(9):509–517, 1975.Google Scholar
Stefan, Berchtold, Daniel A., Keim, and Hans-Peter, Kriegel. The x-tree: an index structure for high-dimensional data. In VLDB '96: Proceedings of the 22th International Conference on Very Large Data Bases, pages 28–39, 1996.
Stefan, Berchtold, Christian, Böhm, and Hans-Peter, Kriegel. The pyramid-tree: Breaking the curse of dimensionality. In SIGMOD 1998. Proceedings ACM SIGMOD International Conference on Management of Data, pages 142–153, 1998.
Adam, Berger and John, Lafferty. Information retrieval as statistical translation. In Proceedings of the 1999 ACM SIGIR Conference on Research and Development in Information Retrieval, pages 222–229, 1999.
Francisco José, Berlanga, María José, del Jesús, María José, Gacto, and Francisco, Herrera. A genetic-programming-based approach for the learning of compact fuzzy rule-based classification systems. In ICAISC, pages 182–191, 2006.
Michael W., Berry, Susan T., Dumais, and Todd A., Letsche. Computational methods for intelligent information access. In Proceedings of the 1995 ACM/IEEE Supercomputing Conference, 1995.
S., Beucher. Watersheds of functions and picture segmentation. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, pages 1928–1931, 1982.
S., Beucher and C., Lantuejoul. Use of watersheds in contour detection. In Proceedings of the International Workshop on Image Processing, Real-Time Edge and Motion Detection/Estimation, 1979.
S., Beucher and F., Meyer. The morphological approach of segmentation: The watershed transformation. chapter 12. pages 1928-1931. 1992.
Kevin S., Beyer, Jonathan Goldstein, Raghu Ramakrishnan, and Uri Shaft. When is “nearest neighbor” meaningful? In ICDT '99: Proceedings of the 7th International Conference on Database Theory, pages 217-235. Springer-Verlag, 1999.
Gaurav, Bhalotia, Charuta, Nakhe, Arvind, Hulgeri, Soumen Chakrabarti, and S. Sudarshan. Keyword searching and browsing in databases using BANKS. In ICDE, 2002.
Krishna, Bharat and Monika R., Henzinger. Improved algorithms for topic distillation in a hyperlinked environment. In SIGIR '98: Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 104–111, 1998.
P., Bille. A survey on tree edit distance and related problems. Theor. Comput. Sci., 337(1-3):217-239, 2005.Google Scholar
Daniel, Billsus and Michael J., Pazzani. Learning collaborative information filters. In ICML '98: Proceedings of the Fifteenth International Conference on Machine Learning, pages 46–54, 1998.
Alberto Del, Bimbo, Enrico, Vicario, and Daniele, Zingoni. Symbolic description and visual querying of image sequences using spatio-temporal logic. IEEE Trans. Knowl. Data Eng., 7(4):609–622, 1995.Google Scholar
Burton H., Bloom. Space/time trade-offs in hash coding with allowable errors. Commun. ACM, 13(7):422–426, 1970.Google Scholar
J., Blustein, C., Fu, and D. L., Silver. Information visualization for an intrusion detection system. In Proceedings of Hypertext '05, pages 278-279, 2005.
L., Bolduc, J., Culbert, T., Harada, J., Harward, and E., Schlusselberg, The athenamuse 2. functional speciication ceci(mit). report, 1992.
Ravi, Boppana and Magnús M., Halldórsson. Approximating maximum independent sets by excluding subgraphs. BIT, 32(2):180–196, 1992.Google Scholar
Ravi B., Boppana. Eigenvalues and graph bisection: An average-case analysis. In IEEE Symposium on Foundations ofComputer Science, pages 280–285, 1987.
Stephan, Borzsonyi, Konrad, Stocker, and Donald, Kossmann. The skyline operator. In International Conference on Data Engineering, pages 421–430, 2001.
Bernhard E., Boser, Isabelle M., Guyon, and Vladimir N., Vapnik. A training algorithm for optimal margin classifiers. In COLT '92: Proceedings of the Fifth Annual Workshop on Computational Learning Theory, pages 144–152, 1992.
Robert S., Boyer and J. Strother, Moore. A fast string searching algorithm. Commun. ACM, 20(10):762–772, 1977.Google Scholar
Tolga, Bozkaya and Meral, Ozsoyoglu. Indexing large metric spaces for similarity search queries. ACM Trans. Database Syst., 24(3):361–404, 1999.Google Scholar
Paul S., Bradley and O. L., Mangasarian. Feature selection via concave minimization and support vector machines. In ICML '98: Proceedings of the Fifteenth International Conference on Machine Learning, pages 82–90, 1998.
M., Brand. Fast low-rank modiications of the thin singular value decomposition. Linear Algebra Appli., 415(1):20–30, 2006.Google Scholar
M., Brand. A random walks perspective on maximizing satisfaction and proit. In SIAM Conference on Optimization, May 2005.
Matthew, Brand. Incremental singular value decomposition of uncertain data with missing values. In ECCV '02: Proceedings of the 7th European Conference on Computer Vision – Part I, pages 707–720, 2002.
Ulrik, Brandes, Daniel, Delling, Marco, Gaertler, Robert, Gorke, Martin, Hoefer, Zoran, Nikoloski, and Dorothea, Wagner. On modularity clustering. IEEE Trans. Knowl. Data Eng., 20(2):172–188, 2008.Google Scholar
John, Breese, David, Heckerman, and Carl, Kadie. Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings of the 14th Annual Conference on Uncertainty in Artificial Intelligence (UAI-98), pages 43–52, San Francisco, CA, 1998.
Morgan, Kaufmann. Leo, Breiman. Random forests. Mach. Learn., pages 5–32, 2001.
Leo, Breiman. Bagging predictors. Mach. Learn., 24(2):123–140, 1996.Google Scholar
Leo, Breiman, Jerome, Friedman, Charles J., Stone, and R. A., Olshen. Classification and Regression Trees. 1984.
Lee, Breslau, Pei, Cao, Li, Fan, Graham, Phillips, and Scott, Shenker. Web caching and zipf-like distributions: Evidence and implications. In INFOCOM, pages 126–134, 1999.
Richard, Brewer and Margaret, McCann. Laboratory and Field Manual of Ecology. Saunders College Publishing, November 1997.
Sergey, Brin. Near neighbor search in large metric spaces. In VLDB, pages 574–584, 1995.
Sergey, Brin and Lawrence, Page. The anatomy of a large-scale hypertextual web search engine. Comput. Netw. ISDN Syst., 30(1-7):107-117, 1998.Google Scholar
Alan J., Broder. Strategies for eficient incremental nearest neighbor search. Pattern Recogn., 23(1-2):171-178, 1990.Google Scholar
Andrei Z., Broder. On the resemblance and containment of documents. In Compression and Complexity of Sequences (SEQUENCES '97), pages 21-29. IEEE Computer Society, 1997.
Andrei Z., Broder, Steven C., Glassman, Mark S., Manasse, and Geoffrey, Zweig. Syntactic clustering of the Web. Comput. Netw. ISDN Syst., 29(8-13):1157-1166, 1997.Google Scholar
P., Brucker. On the complexity of clustering problems. Optim. Operat. Res., 1977.
M. Cecelia, Buchanan and Polle, Zellweger. Scheduling multimedia documents using temporal constraints. In Proceedings of the Third International Workshop on Network and Operating System Support for Digital Audio and Video, pages 237-249. Springer-Verlag.
M. Cecelia, Buchanan and Polle, Zellweger. Automatically generating consistent schedules for multimedia documents. Multimedia Syst., 1(2):55–67, 1993a.Google Scholar
M. C., Buchanan and P.T., Zellweger. Automatic temporal layout mechanisms. In ACM Multimedia 93, pages 341–350, 1993b.
Michael, Buckland and Fredric, Gey. The relationship between recall and precision. J. Am. Soc. Inf. Sci., 45(1):12–19, 1994.Google Scholar
Chris, Buckley, Gerard, Salton, James, Allan, and Amit, Singhal. Automatic query expansion using smart: Trec 3. In Third Text Retrieval Conference (TREC-3), pages 69-80, 1995.
H., Bunke. Error correcting graph matching: On the influence of the underlying cost function. IEEE Trans. Pattern Anal. Mach. Intell., 21(9):917–922, 1999.Google Scholar
Christopher J. C., Burges. A tutorial on support vector machines for pattern recognition. Data Mining Knowl. Discov., 2:121–167, 1998.Google Scholar
M., Burgin. Generalized Kolmogorov complexity and duality in theory of computations. Not. Russian Acad. Sci., 25(3):19–23, 1982.Google Scholar
W. A., Burkhard and R. M., Keller. Some approaches to best-match ile searching. Commun. ACM, 16(4):230–236, 1973.Google Scholar
A. R., Butz. Alternative algorithm for hilbert's space-filling curve. IEEE Trans. Comput., 20(4):424–426, 1971.Google Scholar
Paul B., Callahan and S. Rao, Kosaraju. A decomposition of multidimensional point sets with applications to k-nearest-neighbors and n-body potential ields. J. ACM, 42(1):67–90, 1995.Google Scholar
Iain, Campbell. Interactive evaluation of the ostensive model using a new test collection of images with multiple relevance assessments. J. Inform. Retri., 2:89–114, 2000a.Google Scholar
Iain, Campbell. The Ostensive Model of Developing Information-Needs. Ph.D. thesis, University of Glasgow, September 2000b.
Iain, Campbell. Supporting information needs by ostensive deinition in an adaptive information space. In MIRO, 1995.
K. Selçuk, Candan and Wen-Syan, Li. On similarity measures for multimedia database applications. Knowl. Inform. Syst., 3(1):30–51, 2001.Google Scholar
K. Selçuk, Candan and Wen-Syan, Li. Reasoning for web document associations and its applications in site map construction. Data Knowl. Eng., 43(2):121–150, 2002.Google Scholar
K. Selçuk, Candan and Wen-Syan, Li. Using random walks for mining web document associations. In PAKDD '00: Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications, pages 294–305, 2000.
K. Selçuk, Candan and Prakash, Yamuna. Similarity-based retrieval of temporal speciications and its application to the retrieval of multimedia documents. Multimedia Tools Appl., 27(1):143–180, 2005.Google Scholar
K. Selçuk, Candan, B., Prabhakaran, and V. S., Subrahmanian. Chimp: a framework for supporting distributed multimedia document authoring and presentation. In Multimedia '96: Proceedings of the Fourth ACM International Conference on Multimedia, pages 329–340, 1996a.
K. Selçuk, Candan, B., Prabhakaran, and V. S., Subrahmanian. Collaborative multimedia documents: authoring and presentation. Int. J. Intel. Syst. Multimedia Comput. Syst., 13:1059–1111, 1996b.Google Scholar
K. Selçuk, Candan, P. Venkat, Rangan, and V. S., Subrahmanian. Collaborative multimedia systems: synthesis of media objects. IEEE Trans. Knowl. Data Eng., 10(3):433–457, 1998.Google Scholar
K. Selçuk, Candan, Eric, Lemar, and V. S., Subrahmanian. View management in multimedia databases. The VLDB Journal, 9(2):131–153, 2000a.Google Scholar
K. Selçuk, Candan, Wen-Syan, Li, and M. Lakshmi, Priya. Similarity-based ranking and query processing in multimedia databases. Data Knowl. Eng., 35(3):259–298, 2000b.Google Scholar
K. Selçuk, Candan, Mehmet E., Donderler, J., Ramamoorthy, and Jong W., Kim. Clustering and indexing of experience sequences for popularity-driven recommendations. In CARPE '06: Proceedings of the 3rd ACM Workshop on Continuous Archival and Retrieval ofPersonal Experiences, pages 75–84, 2006.
K. Selçuk, Candan, Jong Wook, Kim, Huan, Liu, Reshma, Suvarna, and Nitin, Agarwal. Multimedia Data Mining and Knowledge Discovery, chapter, Exploiting spatial transformations for identifying mappings in hierarchical media data. Springer 2007.
K. Selçuk, Candan, Huiping, Cao, Yan, Qi, and Maria Luisa, Sapino. System support for exploration and expert feedback in resolving conflicts during integration of metadata. VLDB J., 17(6):1407–1444, 2008.Google Scholar
K. Selçuk, Candan, Mehmet E., Donderler, Terri, Hedgpeth, Jong Wook, Kim, Qing, Li, and Maria Luisa, Sapino. Sea: Segment-enrich-annotate paradigm for adapting dialog-based content for improved accessibility. TOISACM Trans. Inform. Syst., 27, 3, pages 1-45, May, 2009.Google Scholar
J., Canny. A computational approach to edge detection. Trans. Pattern Anal. Mach. Intell., 8:679–714, 1986.Google Scholar
Huiping, Cao, Yan, Qi, K. Selçuk, Candan, and Maria Luisa, Sapino. Feedback-driven result ranking and query reinement for exploring semi-structured data collections. In EDBT'10:13th International Conference on Extending Database Technology, pages 3-14, 2010.
Jianrong, Cao and A., Cai. A method for classification of scenery documentary using mpeg-7 edge histogram descriptor. VLSI Design and Video Technology, 2005. Proceedings of 2005 IEEE International Workshop on, pages 105–108, 2005.
A. F., Cardenas, I. T., Ieong, R., Barker, R. K., Taira, and C. M., Breant. The knowledge-based object-oriented picquery + language. IEEE Trans. Knowl. Data Eng., 5(4):644–657, 1993.Google Scholar
Michael J., Carey and Donald, Kossmann. Reducing the braking distance of an SQL query engine. In VLDB '98: Proceedings of the 24rd International Conference on Very Large Data Bases, pages 158–169, 1998.
Michael J., Carey and Donald, Kossmann. On saying “enough already!” in SQL. In Proceeding of the ACM SIGMOD Conference on Management of Data, pages 219-230. ACM Press, 1997a.
Michael J., Carey and Donald, Kossmann. Processing top n and bottom n queries. Data Eng. Bull., 20(3) 12-19, 1997b.Google Scholar
J. D., Caroll and J. J., Chang. Analysis of individual diferences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition. Psychometrika, 35 283-319, 1970.Google Scholar
R. G. G., Cattell and Douglas K., Barry, editors. The Object Data Standard: ODMG 3.0.Morgan Kauffman, 2000.
Deepayan, Chakrabarti, Spiros, Papadimitriou, Dharmendra S., Modha, and Christos, Faloutsos. Fully automatic cross-associations. In KDD '04: Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 79–88, 2004.
Kaushik, Chakrabarti and Sharad, Mehrotra. High dimensional feature indexing using hybrid trees. In Proceedings of the 15th IEEE International Conference on Data Engineering (ICDE), pages 440–447, 1999.
Kaushik, Chakrabarti, Venkatesh, Ganti, Jiawei, Han, and Dong, Xin. Ranking objects based on relationships. In SIGMOD Conference, pages 371–382, 2006.
Soumen, Chakrabarti. Mining the Web: Discovering Knowledge from Hypertext Data. Morgan-Kauffman, 2002.
I. M., Chakravarti, R. G., Laha, and J., Roy. Handbook ofMethods of Applied Statistics, volume I. John Wiley and Sons, 1967.
C.-Y., Chan, M., Garofalakis, and R., Rastogi. Re-tree An eficient index structure for regular expressions. In VLDB, 1994.
Chee-Yong, Chan, Pin-Kwang, Eng, and Kian-Lee, Tan. Eficient processing of skyline queries with partially-ordered domains. In ICDE '05: Proceedings of the 21st International Conference on Data Engineering, pages 190–191, 2005a.
Chee-Yong, Chan, Pin-Kwang, Eng, and Kian-Lee, Tan. Stratiied computation of skylines with partially-ordered domains. In SIGMOD '05: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data, pages 203–214, 2005b.
S., Chandrasekaran, B. S., Manjunath, Y. F., Wang, J., Winkeler, and H., Zhang. An eigenspace update algorithm for image analysis. Graph. Models Image Process., 59(5) 321-332, 1997.Google Scholar
C. C., Chang and S. Y., Lee. Retrieval of similar pictures on pictorial databases. Pattern Recogn., 24(7):675–681, 1991.Google Scholar
C. C., Chang. Spatial match retrieval of symbolic pictures. J. Inform. Sci. Eng., 7: 405-422, 1991.Google Scholar
J. W., Chang, J. H., Lee, and Y. J., Lee. Multikey access methods based on term discrimination and signature clustering. SIGIR Forum, 23(SI):176-185, 1989.Google Scholar
J. W., Chang, J. S., Yoo, M. H., Kim, and Y. J., Lee. A signature-based hybrid access scheme for text databases. In International Symposium on Next Generation Database Systems and Their Applications, pages 138–144, 1993.
Kevin Chen-Chuan, Chang and Seung-won, Hwang. Minimal probing: supporting expensive predicates for top-k queries. In SIGMOD '02: Proceedings of the 2002 ACM SIGMOD International Conference on Management of Data, pages 346–357, 2002.
Ning-San, Chang and King-Sun, Fu. Query-by-pictorial-example. IEEE Trans. Softw. Eng., 6(6):519–524, 1980.Google Scholar
S. K., Chang, Q. Y., Shi, and C. W., Yan. Iconic indexing by 2-D strings. IEEE Trans. Pattern Anal. Mach. Intell., 9(3):413–428, 1987.Google Scholar
Shi-Kuo, Chang and Eriand, Jungert. A spatial knowledge structure for image information systems using symbolic projections. In ACM '86: Proceedings of 1986 ACM Fall joint computer conference, pages 79–86, 1986.
Ye-In, Chang, Hsing-Yen, Ann, and Wei-Horng, Yeh. A unique-id-based matrix strategy for efficient iconic indexing of symbolic pictures. Pattern Recogn., 33(8): 1263-1276, 2000a.Google Scholar
Y. I., Chang and B. Y., Yang. A prime-number-based matrix strategy for efficient iconic indexing of symbolic pictures. Pattern Recogn., 30(10):1–13, 1997.Google Scholar
Y. I., Chang, B. Y., Yang, and W. H., Yeh. A generalized prime-number-based matrix strategy for efficient iconic indexing of symbolic pictures. Pattern Recogn. Lett., 22:657–666, 2001.Google Scholar
Y. I., Chang, B. Y., Yang, and W. H., Yeh. A bit-pattern-based matrix strategy for efficient iconic indexing of symbolic pictures. Pattern Recogn. Lett., 24:537–545, 2003.Google Scholar
Yuan-Chi, Chang, Lawrence, Bergman, Vittorio, Castelli, Chung-Sheng, Li, MingLing, Lo, and John R., Smith. The onion technique: indexing for linear optimization queries. In SIGMOD '00: Proceedings of the 2000 ACM SIGMOD international conference on Management ofdata, pages 391–402, 2000b.
Moses S., Charikar. Similarity estimation techniques from rounding algorithms. In STOC '02: Proceedings of the Thirty-fourth Annual ACM Symposium on Theory of Computing, pages 380–388, 2002.
B. B., Chaudhuri and N., Sarkar. Texture segmentation using fractal dimension. PAMI, 17(1):72–77, January 1995.Google Scholar
S., Chaudhuri, L., Gravano, and Amlie, Marian. Optimizing top-k selection queries over multimedia repositories. IEEE Trans. Knowl. Data Eng, 16(8):992–1009, 2004.Google Scholar
Surajit, Chaudhuri. An overview of query optimization in relational systems. In PODS '98: Proceedings of the Seventeenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles ofDatabase Systems, pages 34–43, 1998.
Surajit, Chaudhuri and Luis, Gravano. Evaluating top-k selection queries. In VLDB'99, Proceedings of 25th International Conference on Very Large Data Bases, September 7-10, 1999, Edinburgh, Scotland, UK, pages 397–410, 1999.
Edgar, Chavez, Gonzalo, Navarro, Ricardo, Baeza-Yates, and Jose L., Marroquin. Searching in metric spaces. ACM Comput. Surv., 33:273–321, 1999.Google Scholar
S., Chawathe. Comparing Hierarchical Data in External Memory. In Twenty-fifth International Conference on Very Large Data Bases, Edinburgh, Scotland, U.K., 1999.
S., Chawathe and H., Garcia-Molina. Meaningful change detection in structured data. In Proceedings of the ACM SIGMOD International Conference on Management of Data, pages 26-37. Tucson, Arizona, May 1997.
R., Chellappa. Two dimensional discrete Gaussian Markov random field models for image processing. In L. N., Kanal and A., Rosenfeld, editors, Progress in Pattern Recognition, volume 2, pages 79-122. North Holland, 1986.
H., Chen and T., Ng. An algorithmic approach to concept exploration in a large knowledge network (automatic thesaurus consultation): symbolic branch-and-bound search vs. connectionist Hopfield net activation. J. Am. Soc. Inf. Sci., 46 (5):348-369, 1995.Google Scholar
Peter Pin-Shan, Chen. The entity-relationship model - toward a unified view of data. ACM Trans. Database Syst., 1(1):9–36, 1976.Google Scholar
Weimin, Chen. More efficient algorithm for ordered tree inclusion. J. Algorithms, 26(2):370–385, 1998.Google Scholar
Reynold, Cheng, Dmitri V., Kalashnikov, and Sunil, Prabhakar. Evaluation of probabilistic queries over imprecise data in constantly-evolving environments. Inform. Syst., 32(1):104–130, 2007.Google Scholar
Venkata S., Cherukuri and K. Selçuk, Candan. Propagation-vectors for trees (pvt): Concise yet effective summaries for hierarchical data and trees. In CIKM Workshop on Large-Scale Distributed Systems for Information Retrieval (LSDS-IR), 2008.
David Maxwell, Chickering, David, Heckerman, and Christopher, Meek. A Bayesian approach to learning Bayesian networks with local structure. In Proceedings of Thirteenth Conference on Uncertainty in Artificial Intelligence, pages 80–89, 1997.
Jan, Chomicki. Preference formulas in relational queries. ACM Trans. Database Syst., 28(4):427–466, 2003.Google Scholar
Jan, Chomicki, Parke, Godfrey, Jarek, Gryz, and Dongming, Liang. Skyline with presorting. In ICDE, pages 717–719, 2003.
Jan, Chomicki, Parke, Godfrey, Jarek, Gryz, and Dongming, Liang. Skyline with presorting: Theory and optimizations. In Intelligent Information Systems, pages 595604, 2005.
Wesley W., Chu, Chih-Cheng, Hsu, Ion Tim, Ieong, and Ricky K., Taira. Content-based image retrieval using metadata and relaxation techniques. In Multimedia Data Management, pages 149-190. 1998.
Fan R. K., Chung. Spectral Graph Theory. American Mathematical Society, 1997.
P., Ciaccia, M., Patella, F., Rabitti, and P., Zezula. P. Indexing metric spaces with Mtree. In Proc. Quinto convegno Nazionale Sistemi Evolutiper Basi di Dati, pages 67-86, 1997.
Paolo, Ciaccia and Marco, Patella. Pac nearest neighbor queries: Approximate and controlled search in high-dimensional and metric spaces. In ICDE, pages 244–255, 2000.
Rudi, Cilibrasi and Paul M. B., Vitanyi. Clustering by compression. IEEE Trans. Inform. Theory, 51(4):1523–1545, 2005.Google Scholar
Kenneth L., Clarkson. An algorithm for approximate closest-point queries. In SCG '94: Proceedings of the Tenth Annual Symposium on Computational Geometry, pages 160–164, 1994.
E. F., Codd. A relational model of data for large shared data banks. Commun. ACM, 13(6):377–387, 1970.Google Scholar
William W., Cohen, Robert E., Schapire, and Yoram, Singer. Learning to order things. In NIPS '97: Proceedings of the 1997 Conference on Advances in Neural Information Processing Systems 10, pages 451–457, 1998.
Richard, Cole. Tight bounds on the complexity of the Boyer-Moore string matching algorithm. SIAM J. Comput., 23(5), 1994.Google Scholar
Allan M., Collins and Elizabeth F., Loftus. A spreading-activation theory of semantic processing. Psychol. Rev., 82(6):407–428, 1975.Google Scholar
Beate, Commentz-Walter. A string matching algorithm fast on the average. In Proceedings of the 6th Colloquium on Automata, Languages and Programming, pages 118-132, London, UK, 1979. Springer-Verlag.
F., Commoner, A. W., Holt, S., Even, and A., Pnueli. Marked directed graphs. J. Comp. Syst. Sci., 5(5):511–523, 1971.Google Scholar
Thomas H., Cormen, Charles E., Leiserson, Ronald L., Rivest, and Clifford, Stein. Introduction to Algorithms, Second Edition. McGraw-Hill Science/Engineering/ Math, July 2001. ISBN 0070131511.
G., Cormode and S., Muthukrishnan. The string edit distance matching problem with moves. In ACM-SIAM Symposium on Discrete Algorithms, 2002.
M., Crochemore and R., Vrin. Direct construction of compact directed acyclic word graphs. In CPM97, pages 116–12. LNCS 1264, Springer-Verlag, 1997.
M., Crochemore, A., Czumaj, L., Gasieniec, S., Jarominek, T., Lecroq, W., Plandowski, and W., Rytter. Speeding up two string-matching algorithms. Algorithmica, 12 (4/5):247-267, October 1994.Google Scholar
W. B., Croft and D. J., Harper. Using probabilistic models of document retrieval without relevance information. In Readings in information Retrieval, K. Sparck, Jones and P., Willett, Eds., Morgan Kaufmann Multimedia Information And Systems Series, Morgan Kaufmann Publishers, San Francisco, CA, pages 339-344, 1997.
W. B., Croft and D. J., Harper. Using probabilistic models of document retrieval without relevance information. J. Documentation, 35:285–295, 1979.Google Scholar
G. R., Cross and A. K., Jain. Markov random field texture models. TransPAMI, 5: 25-39, 1983.Google Scholar
Nilesh N., Dalvi and Dan, Suciu. Management of probabilistic data: foundations and challenges. In PODS, pages 1–12, 2007.
N. N., Dalvi and D., Suciu. Efficient query evaluation on probabilistic databases. In Proceedings of VLDB '04, pages 864–875, 2004.
Fred J., Damerau. A technique for computer detection and correction of spelling errors. Commun. ACM, 7(3):171–176, 1964.Google Scholar
Nabil Hachem Daniel J., Abadi, and Samuel R., Madden. Column-stores vs. row-stores: how different are they really? In SIGMOD, Vancouver, Canada, 2008.
George, Dantzig. Linear Programming and Extensions. Princeton University Press, 1963.
Mayur, Datar, Nicole, Immorlica, Piotr, Indyk, and Vahab S., Mirrokni. Locality-sensitive hashing scheme based on p-stable distributions. In SCG '04: Proceedings of the Twentieth Annual Symposium on Computational Geometry, pages 253–262, 2004.
G., Davis. Self-quantized wavelet subtrees: a wavelet-based theory for fractal image compression. Data Compression Conference, 232, 1995.
Jesse, Davis and Mark, Goadrich. The relationship between precision-recall and roc curves. In ICML '06: Proceedings of the 23rd International Conference on Machine Learning, pages 233–240, 2006.
Young Francis, Day, Serhan, Dagtas, Mitsutoshi, Iino, Ashfaq A., Khokhar, and Arif, Ghafoor. Spatio-temporal modeling of video data for on-line object-oriented query processing. In ICMCS, pages 98–105, 1995a.
Young Francis, Day, Serhan, Dagtas, Mitsutoshi, Iino, Ashfaq A., Khokhar, and Arif, Ghafoor. An object-oriented conceptual modeling of video data. In ICDE '95: Proceedings of the Eleventh International Conference on Data Engineering, pages 401-408. IEEE Computer Society, 1995b.
D., Dasgupta and F. A., Gonzalez. An intelligent decision support system for intrusion detection and response. In Proceedings of MMM-ACNS'01, 2001.
Ronaldo Mussauer, de Lima, Flavio Paiva, Junqueira, Paulo Andre da S., Goncalves, and Otto Carlos Muniz B., Duarte. Samm: An integrated environment to support multimedia synchronization of pre-orchestrated data. In ICMCS '99: Proceedings of the IEEE International Conference on Multimedia Computing and Systems, Volume 2, page 929. IEEE Computer Society, 1999.
H., Debar, M., Dacier, and A., Wespi. Towards a taxonomy of intrusion-detection systems. Comp. Networks, 31:805–822, 1999.Google Scholar
Rina, Dechter, Itay, Meiri, and Judea, Pearl. Temporal constraint networks. Artifi. Intell., 49(1-3):61-95, 1991.Google Scholar
S., Deerwester, Susan Dumais, G. W. Furnas, T. K., Landauer, and R., Harshman. Indexing by latent semantic analysis. J. Am. Soc. Inform. Sci., 41(6):391–407, 1990.Google Scholar
A. P., Dempster, N. M., Laird, and D. B., Rubin. Maximum likelihood from incomplete data via the em algorithm. J. R. Statist. Soc. Ser. B (Methodol.), 39(1):1–38, 1977.Google Scholar
P., Desain. A (de)composable theory of rhythm. Music Perception, 9(4):439–454, 1992.Google Scholar
Mukund, Deshpande and George, Karypis. Item based top-n recommendation algorithms. ACM Trans. Inform. Syst., 22:143–177, 2004.Google Scholar
Luc, Devroye and Louise, Laforest. An analysis of random d-dimensional quad trees. SIAM J. Comput., 19(5):821–832, 1990.Google Scholar
Inderjit S., Dhillon, Subramanyam, Mallela, and Dharmendra S., Modha. Information-theoretic co-clustering. In KDD '03: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 89–98, 2003.
Thomas G., Dietterich. An experimental comparison of three methods for constructing ensembles of decision trees: bagging, boosting, and randomization. Mach. Learn., 40(2):139–157, 2000.Google Scholar
B., Ding, J. X., Yu, S., Wang, L., Qing, X., Zhang, and X., Lin. Finding top-& min-cost connected trees in databases. In ICDE, 2007.
Chris, Ding and Xiaofeng, He. K-means clustering via principal component analysis. In ICML '04: Proceedings of the Twenty-first International Conference on Machine Learning, pages 225–232, 2004.
Ajay, Divakaran. An overview of MPEG-7 motion descriptors and their applications. In Proceedings of the 9th International Conference on Computer Analysis of Images and Patterns (CAIP'01), 29-40, 2001.
Donko, Donjerkovic and Raghu, Ramakrishnan. Probabilistic optimization of top n queries. In VLDB '99: Proceedings of the 25th International Conference on Very Large Data Bases, pages 411–422, 1999.
P., Drineas, Alan, Frieze, Ravi, Kannan, Santosh, Vempala, and V., Vinay. Clustering in large graphs and matrices. In SODA '99: Proceedings of the Tenth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 291–299, 1999.
Petros, Drineas, Ravi, Kannan, and Michael W., Mahoney. Fast Monte Carlo algorithms for matrices III: computing a compressed approximate matrix decomposition. SIAMJ. Comput., 36(1):184–206, 2006a.Google Scholar
Petros, Drineas, Michael W., Mahoney, and S., Muthukrishnan. Subspace sampling and relative-error matrix approximation: column-row-based methods. In ESA'06: Proceedings of the 14th Annual European Symposium on Algorithms, pages 304–314, 2006b.
Didier, Dubois and Henri, Prade. What are fuzzy rules and how to use them. Fuzzy Sets Syst., 84:169–185, 1996.Google Scholar
M. P., Dubuisson and R. C., Dubes. Efficacy of fractal features in segmenting images of natural textures. PRL, 15(4):419–431, April 1994.Google Scholar
R. O., Duda and P. E., Hart. Use of the Hough transformation to detect lines and curves in pictures. Commun. ACM, 15:11–15, 1972.Google Scholar
Cynthia, Dwork, Ravi, Kumar, Moni, Naor, and D., Sivakumar. Rank aggregation methods for the web. In WWW '01: Proceedings of the 10th International Conference on World Wide Web, pages 613–622, 2001.
H., Edelsbrunner. A new approach to rectangle intersections, part i. Int. J. Computer Mathematics, 13:209–219, 1983a.Google Scholar
H., Edelsbrunner. A new approach to rectangle intersections, part ii. Int. J. Computer Mathematics, 13:221–229, 1983b.Google Scholar
M., Egenhofer. Deriving the composition of binary topological relations. J. Visual Lang. Comput., 5(2):133–149, 1994.Google Scholar
Essam A., El-Kwae and Mansur R., Kabuka. A robust framework for content-based retrieval by spatial similarity in image databases. ACM Trans. Inf. Syst., 17(2): 174-198, 1999.Google Scholar
I. M., Elfadel and R. W., Picard. Gibbs random fields, cooccurrences and texture modeling. IEEE Trans. Pattern Anal. Mach. Intell., 16(1):24–37, 1994.Google Scholar
Daniel P., Ellis. Beat tracking by dynamic programming. J. New Music Res., 36(1): 51-60, 2007.Google Scholar
Dominik M., Endres and Johannes E., Schindelin. A new metric for probability distributions. IEEE Trans. Inform. Theory, 49(7):1858–1860, 2003.Google Scholar
P., Erdos and A., Renyi. On random graphs. Pub. Math., 6:290–297, 1959.Google Scholar
Martha, Escobar-Molano, David A., Barrett, Zornitza, Genova, and Lei, Zhang. Retrieval scheduling for multimedia presentations. In Multimedia Information Systems, pages 143–152, 2001.
Ronald, Fagin. Combining fuzzy information from multiple systems. In Proceedings of the ACM Symposium on Principles ofDatabase Systems, pages 216–226, 1996.
Ronald, Fagin. Fuzzy queries in multimedia database systems. In PODS, pages 1–10, 1998.
Ronald, Fagin and Yoelle S., Maarek. Allowing users to weight search terms. In Proceedings of Recherche d'Informations Assistee par Ordinateur RIAO '2000, pages 682-700, 2000.
Ronald, Fagin and Edward L., Wimmers. Incorporating user preferences in multimedia queries. In ICDT, pages 247–261, 1997.
Ronald, Fagin, Amnon, Lotem, and Moni, Naor. Optimal aggregation algorithms for middleware. In PODS, 2001.
Ronald, Fagin, Amnon, Lotem, and Moni, Naor. Optimal aggregation algorithms for middleware. J. Comput. Syst. Sci., 66(4):614–656, 2003.Google Scholar
C., Faloutsos, R., Barber, M., Flickner, J., Hafner, W., Niblack, D., Petkovic, and W., Equitz. Efficient and effective querying by image content. J. Intell. Inform. Syst., 3(3-4):231-262, 1994.Google Scholar
Christos, Faloutsos. Signature files. Information Retrieval: Data Structures & Algorithms, pages 44-65, 1992.
Christos, Faloutsos and Stavros, Christodoulakis. Design of a signature file method that accounts for non-uniform occurrence and query frequencies. In VLDB '1985: Proceedings of the 11th International Conference on Very Large Data Bases, pages 165–170, 1985.
Christos, Faloutsos and H. V., Jagadish. Hybrid index organizations for text databases. In EDBT '92: Proceedings of the 3rd International Conference on Extending Database Technology, pages 310–327, 1992.
Christos, Faloutsos and King-Ip, Lin. Fast Map: a fast algorithm for indexing, data-mining and visualization of traditional and multimedia datasets. In SIGMOD '95: Proceedings of the 1995 ACM SIGMOD International Conference on Management ofData, pages 163–174, 1995.
Christos, Faloutsos and Shari, Roseman. Fractals for secondary key retrieval. Technical Report UMIACS-TR-89-47, University of Maryland, 1989.
Christos, Faloutsos and Hanghang, Tong. Large graph mining: patterns, tools and case studies. Tutorial at ICDE 2009, 2009.
Gunnar, Fant. Analysis and synthesis of speech processes. In Manual of Phonetics, 1968.
M., Farach and M., Thorup. Sparse dynamic programming for evolutionary-tree comparison. SIAM J. Comput., 26(1):210–230, January 1997.Google Scholar
W. Y., Feng, Y. B., Yan, G. G., Huang, and G. F., Jin. Micro-optical multiwavelet element for hybrid texture segmentation processor. Opt Eng, 37(1):185–188, January 1998.Google Scholar
T. S., Ferguson. A Bayesian analysis of some nonparametric problems. Ann. Statist., 1(2):209–230, 1973.Google Scholar
Hakan, Ferhatosmanoglu, Ertem, Tuncel, Divyakant, Agrawal, and Amr El, Abbadi. Vector approximation based indexing for non-uniform high dimensional data sets. In CIKM '00: Proceedings of the Ninth International Conference on Information and Knowledge Management, pages 202–209, 2000.
C. M., Fiduccia and R. M., Mattheyses. A linear-time heuristic for improving network partitions. In 25 years of DAC: Papers on Twenty-five Years of Electronic Design Automation, pages 241–247, 1988.
M., Fiedler. Algebraic connectivity of graphs. Czech. Math. J., 23(98):298–305, 1973.Google Scholar
M., Fiedler. A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory. Czech. Math. J., 25:619–637, 1975.Google Scholar
R. A., Finkel and J. L., Bentley. Quad trees: a data structure for retrieval on composite keys. Acta Inform., 4:1–9, 1974.Google Scholar
G., Fischer. User modeling in human-computer interaction. In User Modeling and User-Adapted Interaction, 2001.
Gary W., Flake, Robert E., Tarjan, and Kostas, Tsioutsiouliklis. Graph clustering and minimum cut trees. Internet Math., 1(4):385–408, 2004.Google Scholar
Gary William, Flake, Steve, Lawrence, and C. Lee, Giles. Efficient identification of web communities. In KDD '00: Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 150–160, 2000.
Sergio, Flesca, Giuseppe, Manco, Elio, Masciari, and Luigi, Pontieri. Fast detection of XML structural similarity. IEEE Trans. Knowl. Data Eng., 17(2):160–175, 2005. Student Member-Andrea Pugliese.Google Scholar
Myron, Flickner, Harpreet, Sawhney, Wayne, Niblack, Jonathan, Ashley, Qian, Huang, Byron, Dom, Monika, Gorkani, Jim, Hafner, Denis, Lee, Dragutin, Petkovic, David, Steele, and Peter, Yanker. Query by image and video content: The qbic system. Computer, 28(9):23–32, 1995.Google Scholar
G. D., Forney. The viterbi algorithm. In Proceedings of the IEEE, volume 61, pages 268-278, March 1973.Google Scholar
W. N., Francis and H., Kucera. Frequency Analysis of English Usage: Lexicon and Grammar. Houghton Mifflin, 1982.
Edward, Fredkin. Trie memory. Commun. ACM, 3(9):490–499, 1960.Google Scholar
H., Freeman. Use of incremental curvature for describing and analyzing two-dimensional shape. In PRIP79, pages 437–444, 1979.
H., Freeman. Boundary encoding revisited. In AIU96, pages 84–91, 1996.
William, Freeman and Edward H., Adelson Y. The design and use of steerable filters. IEEE Trans. Pattern Anal. Mach. Intel., 13:891–906, 1991.Google Scholar
Yoav, Freund and Robert E., Schapire. Large margin classification using the perceptron algorithm. In COLT '98: Proceedings of the Eleventh Annual Conference on Computational Learning Theory, pages 209–217, 1998.
Yoav, Freund and Robert E., Schapire. A decision-theoretic generalization of online learning and an application to boosting. In EuroCOLT '95: Proceedings of the Second European Conference on Computational Learning Theory, pages 23–37, 1995.
Yoav, Freund and Robert E., Schapire. A decision-theoretic generalization of on-line learning and an application to boosting. J. Comp. Syst. Sci., 55(1):119–139, 1997.Google Scholar
Yoav, Freund, Raj, Iyer, Robert E., Schapire, and Yoram, Singer. An efficient boosting algorithm for combining preferences. J. Mach. Learn. Res., pages 170–178, 2003.
Jerome H., Friedman, Jon Louis, Bentley, and Raphael Ari, Finkel. An algorithm for finding best matches in logarithmic expected time. ACM Trans. Math. Softw., 3 (3):209-226, 1977.Google Scholar
Alan, Frieze, Ravi, Kannan, and Santosh, Vempala. Fast Monte-Carlo algorithms for finding low-rank approximations. In FOCS '98: Proceedings of the 39th Annual Symposium on Foundations of Computer Science, pages 370–378, 1998.
Henry, Fuchs, Zvi M., Kedem, and Bruce F., Naylor. On visible surface generation by a priori tree structures. SIGGRAPH Comput. Graph., 14(3):124–133, 1980.Google Scholar
Keinosuke, Fukunaga and Patrenahalli M., Narendra. A branch and bound algorithms for computing k-nearest neighbors. IEEE Trans. Comput., 24(7):750–753, 1975.Google Scholar
Ombretta, Gaggi and Augusto, Celentano. Modelling synchronized hypermedia presentations. Multimedia Tools Appl., 27(1):53–78, 2005.Google Scholar
S. I., Gallant. Optimal linear discriminants. In Eighth International Conference on Pattern Recognition, pages 849–852, 1986.
N., Garg, G., Konjevod, and R., Ravi. A polylogarithmic approximation algorithm for the group Steiner tree problem. In Proceedings of the 9th Annual ACM-SIAM Symposium on Discrete Algorithms, pages 253–259, 1998.
J., Gemmell, G., Bell, and R., Lueder. Mylifebits: a personal database for everything. CACM, 49(1):88–95, 2006.Google Scholar
Simon J., Gibbs, Christian, Breiteneder, and Dennis, Tsichritzis. Audio/video databases: An object-oriented approach. In Proceedings of the Ninth International Conference on Data Engineering, pages 381–390, 1993.
David, Gibson, Jon, Kleinberg, and Prabhakar, Raghavan. Inferring web communities from link topology. In HYPERTEXT '98: Proceedings of the Ninth ACM Conference on Hypertext and Hypermedia: Links, Objects, Time and Space – Structure in Hypermedia Systems, pages 225–234, 1998.
Rosalba, Giugno and Dennis, Shasha. Graphgrep: a fast and universal method for querying graphs. In Proceeding of the IEEE International Conference on Pattern Recognition (ICPR), pages 112–115, 2002.
Parke, Godfrey, Ryan, Shipley, and Jarek, Gryz. Maximal vector computation in large data sets. In VLDB, pages 229–240, 2005.
Martin, Gogolla and Uwe, Hohenstein. Towards a semantic view of an extended entity-relationship model. ACM Trans. Database Syst., 16(3):369–416, 1991.Google Scholar
David, Goldberg, David, Nichols, Brian M., Oki, and Douglas, Terry. Using collaborative filtering to weave an information tapestry. Commun. ACM, 35(12):61–70, 1992.Google Scholar
R. E., Gomory and T. C., Hu. Multi-terminal network flows. J. SIAM, 9:551–570, 1961.Google Scholar
C., Goodall. Procrustes methods in the statistical analysis of shape. J. R. Statist. Soc. Ser. B (Methodol), 53(2):285–339, 1991.Google Scholar
Luc J., Van Gool, Theo Moons, and Dorin Ungureanu. Affine/ photometric invariants for planar intensity patterns. In ECCV '96: Proceedings of the 4th European Conference on Computer Vision, Volume I, pages 642–651, 1996.
J., Gower. Generalized Procrustes analysis. Psychometrika, 40:33–51, 1975.Google Scholar
Luis, Gravano, Amelie, Marian, and Surajit, Chaudhuri. Optimizing top-k selection queries over multimedia repositories. IEEE Trans. Knowl. Data Eng., 16(8):992–1009, 2004.Google Scholar
Todd J., Green and Val, Tannen. Models for incomplete and probabilistic information. IEEE Data Eng. Bull., 29, 2006.Google Scholar
S., Grinaker. Edge based segmentation and texture separation. In Proceedings of the 5th International Conference on Pattern Recognition, pages 554–557, 1980.
Matthias, Gruhne, Ruben, Tous, Jaime, Delgado, Mario, Doeller, and Harald, Kosch. Mp7qf: An Mpeg-7 query format. In AXMEDIS '07: Proceedings of the Third International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution, pages 15–18, 2007.
Xiaohui, Gu and Klara, Nahrstedt. Distributed multimedia service composition with statistical qos assurances. IEEE Transactions on Multimedia, 8(1):141–151, 2006.Google Scholar
Xiaohui, Gu and Philip S., Yu. Toward self-managed media stream processing service overlays. In ICME, pages 2054–2057, 2007.
Ming, Gu and Stanley C., Eisenstat. Downdating the singular value decomposition. SIAM J. Matrix Anal. Appl., 16(3):793–810, 1995.Google Scholar
Ming, Gu and Stanley C., Eisenstat. A stable and fast algorithm for updating the singular value decomposition. Technical report, YALEU/DCS/RR-966, Department of Computer Science, Yale University, New Haven, CT, 1993.
Venkat N., Gudivada. Theta R-string: a geometry-based representation for efficient and effective retrieval of images by spatial similarity. IEEE Trans. Knowl. Data Eng., 10(3):504–512, 1998.Google Scholar
Venkat N., Gudivada and Vijay V., Raghavan. Design and evaluation of algorithms for image retrieval by spatial similarity. ACM Trans. Inform. Syst., 13:115–144, 1995.Google Scholar
Ulrich, Güntzer, Wolf-Tilo, Balke, and Werner, Kiessling. Optimizing multi-feature queries for image databases. In VLDB '00: Proceedings of the 26th International Conference on Very Large Data Bases, pages 419–428, 2000.
Ulrich, Güntzer, Wolf-Tilo, Balke, and Werner, Kiessling. Towards efficient multifeature queries in heterogeneous environments. In ITCC '01: Proceedings of the International Conference on Information Technology: Coding and Computing, pages 622–628, 2001.
Sha, Guo, Wei, Sun, Yi, Deng, Wei, Li, Qing, Liu, and Weiping, Zhang. Panther: an inexpensive and integrated multimedia environment. Proceedings of the International Conference on Multimedia Computing and Systems, 1994, pages 382–391, May 1994.
Zhen, Guo, Zhongfei, Zhang, Eric, Xing, and Christos, Faloutsos. Enhanced max margin learning on multimodal data mining in a multimedia database. In KDD '07: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 340–349, 2007.
Peter, Gursky and Peter, Vojtas. Speeding up the NRA algorithm. In SUM '08: Proceedings of the 2nd International Conference on Scalable Uncertainty Management, pages 243–255, 2008.
Antomn, Guttman. R-trees: a dynamic index structure for spatial searching. In Proceedings of the 1984 ACM SIGMOD International Conference on Management of Data, pages 47–57, 1984.
A., Haar. Zur theorie der orthogonalen Funktionensysteme. Math. Ann., 69:331–371, 1910.Google Scholar
Peter J., Haas and Joseph M., Hellerstein. Ripple joins for online aggregation. SIG-MOD Rec., 28(2):287–298, 1999.Google Scholar
James L., Hafner, Harpreet S., Sawhney, William, Equitz, Myron, Flickner, and Wayne, Niblack. Efficient color histogram indexing for quadratic form distance functions. IEEE Trans. Pattern Anal. Mach. Intell., 17(7):729–736, 1995.Google Scholar
Veli, Hakkoymaz and Gultekin, Ozsoyoglu. A constraint-driven approach to automate the organization and playout of presentations in multimedia databases. Multimedia Tools AppL, 4(2):171–197, 1997.Google Scholar
Veli, Hakkoymaz, J., Kraft, and G., Ozsoyoglu. Constraint-based automation of multimedia presentation assembly. ACM Multimedia Syst. J., 7:500–518, 1999.Google Scholar
Rei, Hamakawa and Jun, Rekimoto. Object composition and playback models for handling multimedia data. In MULTIMEDIA '93: Proceedings of the First ACM International Conference on Multimedia, pages 273–281, 1993.
Greg, Hamerly and Charles, Elkan. Learning the k in k-means. In Proceedings of the 17th NIPS, pages 281–288, 2003.
Richard W., Hamming. Error detecting and error correcting codes. Bell Syst. Tech. J., 26(2):147–160, 1950.Google Scholar
J., Han and M., Kamber. Data Mining: Concepts and Techniques. Morgan Kauffman, 2001.
Mark H., Hansen and Bin, Yu. Model selection and the principle of minimum description length. J. Am. Statist. Assoc., 96(454):746–774, 2001.Google Scholar
Frank, Harary and Allen J., Schwenk. The spectral approach to determining the number of walks in a graph. Pacific J. Math., 80(2):443–449, 1979.Google Scholar
Donna, Harman, Edward A., Fox, Ricardo A., Baeza-Yates, and Whay C., Lee. Inverted files. In Information Retrieval: Data Structures & Algorithms, pages 28-43. 1992.
R. A., Harshman. Foundations of the parafac procedure: models and conditions for an” explanatory” multi-modal factor analysis. UCLA Working Papers Phonet., 16:1–84, 1970.Google Scholar
M., Hassner and J., Sklansky. The use of Markov random fields as models of textures. Comp. Graph. Image Proc., 12:357–370, 1980.Google Scholar
Peter E., Hart, Nils J., Nilsson, and Bertram, Raphael. Correction to “a formal basis for the heuristic determination of minimum cost paths.” SIGART Bull., (37):28-29, 1972.Google Scholar
Bin, He and Kevin Chen-Chuan, Chang. Automatic complex schema matching across web query interfaces: A correlation mining approach. ACM Trans. Database Syst., 31(1):346–395, 2006.Google Scholar
D., Hebb. Organisation of Behaviour. John Wiley & Sons, 1949.
Nevin, Heintze. Scalable document fingerprinting. In USENIX Workshop on Electronic Commerce, 1996.
Joseph M., Hellerstein. Optimization techniques for queries with expensive methods. ACM Trans. Database Syst., 23(2):113–157, 1998.Google Scholar
David P., Helmbold and Manfred K., Warmuth. On weak learning. J. Comput. Syst. Sci., 50(3):551–573, 1995.Google Scholar
Sven, Helmer. Measuring the structural similarity of semistructured documents using entropy. In VLDB '07: Proceedings of the 33rd International Conference on Very Large Data Bases, pages 1022–1032, 2007.
A., Henrich, H. W., Six, and P., Widmayer. The LSD tree: spatial access to multidimensional and non-point objects. In VLDB '89: Proceedings of the 15th International Conference on Very Large Data Bases, pages 45–53, 1989.
Andreas, Henrich. The lsdh-tree: an access structure for feature vectors. In ICDE '98: Proceedings of the Fourteenth International Conference on Data Engineering, pages 362–369, 1998.
Ralf, Herbrich, Thore, Graepel, and Klaus, Obermayer. Large Margin Rank Boundaries for Ordinal Regression. MIT Press, Cambridge, MA, 2000.
Melanie, Herschel and Felix, Naumann. Scaling up duplicate detection in graph data. In CIKM '08: Proceeding of the 17th ACM Conference on Information and Knowledge Management, pages 1325–1326, 2008.
Stacie, Hibino and Elke A., Rundensteiner. A visual query language for identifying temporal trends in video data. In Proceedings of the 1995 International Workshop on Multi-Media Database Management Systems, pages 74–81, 1995.
Stacie, Hibino and Elke A., Rundensteiner. A visual multimedia query language for temporal analysis of video data. In Multimedia Database Systems, pages 123-159. 1996.
David, Hilbert. Über stetige Abbildung einer Linie auf ein Flachenstuck. Math. Ann., 38:459–460, 1891.Google Scholar
Will, Hill, Larry, Stead, Mark, Rosenstein, and George, Furnas. Recommending and evaluating choices in a virtual community of use. In CHI '95: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 194–201, 1995.
Klaus, Hinrichs. Implementation of the grid file: design concepts and experience. BIT, 25(4):569–592, 1985.Google Scholar
Gisli R., Hjaltason and Hanan, Samet. Index-driven similarity search in metric spaces (survey article). ACM Trans. Database Syst., 28(4):517–580, 2003.Google Scholar
Gisli R., Hjaltason and Hanan, Samet. Incremental similarity search in multimedia databases. Technical report, Computer Science Department, University of Maryland, College Park, 2000.
Gísli R., Hjaltason and Hanan, Samet. Distance browsing in spatial databases. ACM Trans. Database Syst., 24(2):265–318, 1999.Google Scholar
Rune, Hjelsvold and Roger, Midtstraum. Modelling and querying video data. In VLDB '94: Proceedings of the 20th International Conference on Very Large Data Bases, pages 686–694, 1994.
Tin Kam, Ho. Complexity of classification problems and comparative advantages of combined classifiers. In Proceedings of the First International Workshop on Multiple Classifier Systems, Lecture Notes in Computer science, pages 97–106, 2000.
Tin Kam, Ho. The random subspace method for constructing decision forests. IEEE Trans. Pattern Anal. Mach. Intell., 20(8):832–844, 1998.Google Scholar
Tin Kam, Ho. Random decision forest. In Proceedings of the 3rd International Conference on Document Analysis and Recognition, pages 278–282, Montreal, Canada, August 1995.
Thomas, Hofmann. Probabilistic latent semantic indexing. In SIGIR '99: Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 50–57, 1999.
Thomas, Hofmann. Learning what people (don't) want. In EMCL '01: Proceedings of the 12th European Conference on Machine Learning, pages 214–225, 2001.
N., Holsti and E., Sutinen. Approximate string matching using q-gram places. In Proceedings of the 7th Finnish Symposium on Computer Science, pages 16-12. University of Joensuu, 1994.
Andre, Holzapfel and Yannis, Stylianou. Rhythmic similarity of music based on dynamic periodicity warping. In ICASSP 2008, pages 2217–2220, 2008.
Wei, Hong and Michael, Stonebraker. Optimization of parallel query execution plans in xprs. Distrib. Parallel Databases, 1(1):9–32, 1993.Google Scholar
John, Hopcroft and Jeffrey, Ullman. Introduction to Automata Theory, Languages, and Computation. Addison-Wesley, 1979.
P. V. C., Hough. Method and means for recognizing complex patterns. U.S. Patent 3, 069, 654, Dec. 18, 1962.
Paul G., Howard and Jeffrey Scott, Vitter. Analysis of arithmetic coding for data compression. In Data Compression Conference, pages 3–12, 1991.
Vagelis, Hristidis, Nick, Koudas, and Yannis, Papakonstantinou. Prefer: a system for the efficient execution of multi-parametric ranked queries. In SIGMOD Conference, pages 259–270, 2001.
Yi-Chung, Hu, Ruey-Shun, Chen, and Gwo-Hshiung, Tzeng. Finding fuzzy classification rules using data mining techniques. Pattern Recogn. Lett., 24(1-3):509-519, 2003.Google Scholar
P. W., Huang and Y. R., Jean. Using 2D C+-string as spatial knowledge representation for image database systems. Pattern Recogn., (27):1249-1257, 1994.
Zan, Huang, Hsinchun, Chen, and Daniel, Zeng. Applying associative retrieval techniques to alleviate the sparsity problem in collaborative filtering. ACM Trans. Inform. Syst., 22:116–142, 2004.Google Scholar
D. A., Huffman. A method for the construction of minimum-redundancy codes. Proc. IRE, 40(9):1098–1101, 1952.Google Scholar
John E., Hutchinson. Fractals and self similarity. Indiana Univ. Math. J., 30:713–747, 1981.Google Scholar
Eenjun, Hwang and V. S., Subrahmanian. Querying video libraries. J. Visual Commun. Image Representation, 7(1):44–60, 1996.Google Scholar
A., Hyvärinen. Survey on independent component analysis. Neural Comput. Surv., 2:94–128, 1999.Google Scholar
E., Ide and G., Salton. New Experiments in Relevance Feedback, chapter 16, in The Smart Retrieval System - Experiments in Automatic Document Processing, Prentice-Hall, pages 337-354. 1971a.
E., Ide and G., Salton. Interactive Search Strategies and Dynamic File Organization in Information Retrieval, chapter 18, in The Smart Retrieval System – Experiments in Automatic Document Processing, Prentic-Hall, pages 373-393. 1971b.
E., Ihler. Bounds on the quality of approximate solutions to the group Steiner tree problem. In Proceedings of the 16th International Workshop on Graph Theoretic Concepts in Computer Science. Lecture Notes in Computer Science, pages 109–118, 1991.
Mitsutoshi, Iino, Young Francis, Day, and Arif, Ghafoor. An object-oriented model for spatio-temporal synchronization of multimedia information. In ICMCS, pages 110–119, 1994.
N., Ikonomakis, K. N., Plataniotis, and A. N., Venetsanopoulos. Color image segmentation for multimedia applications. J. Intell. Robotics Syst., 28(1-2):5-20, 2000.Google Scholar
Ihab F., Ilyas, Walid G., Aref, and Ahmed K., Elmagarmid. Joining ranked inputs in practice. In VLDB '02: Proceedings of the 28th International Conference on Very Large Data Bases, pages 950–961, 2002.
Ihab F., Ilyas, Walid G., Aref, and Ahmed K., Elmagarmid. Supporting top-& join queries in relational databases. In VLDB, 2003.
Ihab F., Ilyas, G., Aref, and K., Elmagarmid. Supporting top-k join queries in relational databases. VLDB J., 13(3):207–221, 2004a.Google Scholar
Ihab F., Ilyas, Rahul, Shah, Walid G., Aref, Jeffrey Scott, Vitter, and Ahmed K., Elmagarmid. Rank-aware query optimization. In SIGMOD '04: Proceedings of the 2004 ACM SIGMOD International Conference on Management of Data, pages 203-214, 2004b.
Piotr, Indyk and Rajeev, Motwani. Approximate nearest neighbors: towards removing the curse of dimensionality. In STOC '98: Proceedings of the Thirtieth Annual ACM Symposium on Theory of Computing, pages 604–613, 1998.
H., Ishibuchi, T., Nakashima, and T., Murata. Performance evaluation of fuzzy classifier systems for multidimensional pattern classification problems. IEEE Trans. SMC-B, pages 601–618, 1999.
Hemant, Ishwaran and Lancelot F., James. Gibbs sampling methods for stick-breaking priors. J. Am. Statist. Assoc., 96:161–173, 2001.Google Scholar
R., Jain. Experiential computing. CACM, 46(7):48–55, 2003a.Google Scholar
R., Jain. Multimedia electronic chronicles. IEEE MultiMedia, 10(3):111–112, 2003b.Google Scholar
Kristoffer, Jensen. Multiple scale music segmentation using rhythm, timbre, and harmony. EURASIPJ. Appl. Signal Process., 2007(1):159–159, 2007.Google Scholar
Jing, Jiang and Chengxiang, Zhai. Extraction of coherent relevant passages using hidden markov models. ACM Trans. Inform. Syst., 24(3):295–319, 2006.Google Scholar
Tao, Jiang, Lusheng, Wang, and Kaizhong, Zhang. Alignment of trees: an alternative to tree edit. Theor. Comput. Sci., 143(1):137–148, 1995.Google Scholar
Thorsten, Joachims. Optimizing search engines using clickthrough data. In Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 133–142, 2002.
Thorsten, Joachims. Training linear svms in linear time. In KDD '06: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 217–226, 2006.
David S., Johnson and Christos H., Papadimitriou. On generating all maximal independent sets. Inform. Process. Lett., 27(3):119–123, 1988.Google Scholar
Petteri, Jokinen, Jorma, Tarhio, and Esko, Ukkonen. A comparison of approximate string matching algorithms. Softw. Pract. Exper., 26(12):1439–1458, 1996.Google Scholar
T., Joseph and A. F., Cardenas. Picquery: a high level query language for pictorial database management. IEEE Trans. Softw. Eng., 14(5):630–638, 1988.Google Scholar
James E., Coolahan and Nick, Roussopoulos. Timing requirements for time-driven systems using augmented petri nets. IEEE Trans. Softw. Eng., 9(5):603–616, 1983.Google Scholar
Erland, Jungert. Extended symbolic projections as a knowledge structure for spatial reasoning. In Proceedings of the 4th International Conference on Pattern Recognition, pages 343–351, 1988.
Varun, Kacholia, Shashank, Pandit, Soumen, Chakrabarti, S., Sudarshan, Rushi, Desai, and Hrishikesh, Karambelkar. Bidirectional expansion for keyword search on graph databases. In VLDB, pages 505–516, 2005.
Peter K., Kaiser and R.M., Boynton. Human Color Vision, 2nd ed. Optical Society of America, 1996.
Ibrahim, Kamel and Christos, Faloutsos. On packing R-trees. In CIKM '93: Proceedings of the Second International Conference on Information and Knowledge Management, pages 490–499, 1993.
Ibrahim, Kamel and Christos, Faloutsos. Hilbert R-tree: An improved R-tree using fractals. In VLDB '94: Proceedings of the 20th International Conference on Very Large Data Bases, pages 500–509, 1994.
B., Kamgar-Parsi and L. N., Kanal. An improved branch and bound algorithm for computing k-nearest neighbors. Pattern Recogn. Lett, 3(1):7–12, 1985.Google Scholar
R., Kannan, S., Vempala, and A., Veta. On clusterings – good, bad and spectral. In FOCS '00: Proceedings of the 41st Annual Symposium on Foundations of Computer Science, page 367, 2000.
L. M., Kaplan. Extended fractal analysis for texture classification and segmentation. IP, 8(11):1572–1585, November 1999.Google Scholar
L. M., Kaplan and C. C. J., Kuo. Texture segmentation via Haar fractal feature estimation. JVCIR, 6(4):387–400, December 1995.Google Scholar
Richard M., Karp and Michael O., Rabin. Pattern-matching algorithms. IBM J. Res. Dev., 31(2):249–260, 1987.Google Scholar
B., Kartikeyan and A., Sarkar. Shape description by time series. IEEE Trans. Pattern Anal. Mach. Intell., 11(9):977–984, 1989.Google Scholar
George, Karypis and Vipin, Kumar. Multilevel algorithms for multi-constraint graph partitioning. In Supercomputing '98: Proceedings of the 1998 ACM/IEEE Conference on Supercomputing, pages 1–13, 1998.
R., Kashyap and R., Chellappa. Estimation and choice of neighbors in spatial-interaction models of images. IEEE Trans. Inform. Theory, 29(1):60–72, 1983.Google Scholar
R., Kashyap, R., Chellappa, and A., Khotanzad. Texture classification using features derived from random field models. Pattern Recogn. Lett., 1(1):43–50, 1982.Google Scholar
Robert E., Kass and Larry, Wasserman. A reference Bayesian test for nested hypotheses and its relationship to the Schwarz criterion. J. Am. Statist. Assoc., 90: 928-934, 1995.Google Scholar
Norio, Katayama and Shin'ichi, Satoh. The SR-tree: an index structure for high-dimensional nearest neighbor queries. In SIGMOD '97: Proceedings of the 1997 ACM SIGMOD International Conference on Management of Data, pages 369–380, 1997.
N., Katzir, M., Lindenbaum, and M., Porat. Curve segmentation under partial occlusion. IEEE Trans. Pattern Anal. Mach. Intell., 16(5):513–519, May 1994.Google Scholar
S. C., Kau and J., Tseng. MQL- a query language for multimedia databases. In ACM Multimedia, pages 511–516, 1994.
Yan, Ke and Rahul, Sukthankar. PCA-sift: A more distinctive representation for local image descriptors. In Proceedings of the Conference on Computer Vision and Pattern Recognition, pages 506–513, 2004.
J. M., Keller, S. S., Chen, and R. M., Crownover. Texture description and segmentation through fractal geometry. CVGIP, 45(2):150–166, February 1989.Google Scholar
David G., Kendall. Shape manifolds, procrustean metrics, and complex projective spaces. Bull. London Math. Soc., 16(2):81–121, 1984.Google Scholar
M. G., Kendall. A new measure of rank correlation. Biometrika, 30(1/2):81-93, 1938.Google Scholar
A. J., Kent, R., Sacks-Davis, and K., Ramamohanarao. A signature file scheme based on multiple organisations for indexing very large text databases. J. Am. Soc. Inform. Sci., 7(41):508–534, 1990.Google Scholar
B. W., Kernighan and S., Lin. An efficient heuristic procedure for partitioning graphs. Bell Syst. Tech. J., 49(2):291–308, 1970.Google Scholar
J., Kiefer. Sequential minimax search for a maximum. In Proceedings of the American Mathematical Society, volume 4, pages 502-506, 1953.Google Scholar
Werner, Kiessling. Foundations of preferences in database systems. In VLDB '02: Proceedings of the 28th International Conference on Very Large Data Bases, pages 311-322, 2002.
Werner, Kiessling. Preference queries with sv-semantics. In COMAD'05, pages 1526, 2005.
Pekka, Kilpelainen. Tree matching problems with applications to structured text databases. Technical report, University of Helsinki, Finland, 1992.
Pekka, Kilpelainen and Heikki, Mannila. Ordered and unordered tree inclusion. SIAM J. Comput., 24(2):340–356, 1995.Google Scholar
Jong Wook, Kim and K. Selçuk, Candan. Cp/cv: concept similarity mining without frequency information from domain describing taxonomies. In CIKM '06: Proceedings of the 15th ACM International Conference on Information and Knowledge Management, pages 483–492, 2006.
Jong Wook, Kim and K. Selçuk, Candan. Skip-and-prune: Cosine-based top-k query processing for efficient context-sensitive document retrieval. In SIGMOD, 2009.
Jong Wook, Kim, K. Selçuk, Candan, and Junichi, Tatemura. Efficient overlap and content reuse detection in blogs and online news articles. In WWW '09: Proceedings of the 18th International Conference on World Wide Web, pages 81–90, 2009.
Michelle Y., Kim and Junehwa, Song. Multimedia documents with elastic time. In MULTIMEDIA '95: Proceedings of the Third ACM International Conference on Multimedia, pages 143–154, 1995.
M. Y., Kim and J., Song. Hyperstories: combining time, space and asynchrony in multimedia documents. Technical Report RC19277(83726) (revised 1995), IBM Computer Science/Mathematics Research, 1993.
Carolyn, Kimme, Dana, Ballard, and Jack, Sklansky. Finding circles by an array of accumulators. Commun. ACM, 18(2):120–122, 1975.Google Scholar
A., Klapuri. Sound onset detection by applying psychoacoustic knowledge. In ICASSP '99: Proceedings of the 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing, pages 3089–3092, 1999.
Philip N., Klein. Computing the edit-distance between unrooted ordered trees. In ESA '98: Proceedings of the 6th Annual European Symposium on Algorithms, pages 91–102, 1998.
Jon M., Kleinberg. Two algorithms for nearest-neighbor search in high dimensions. In STOC '97: Proceedings of the Twenty-ninth Annual ACM Symposium on Theory ofComputing, pages 599–608, 1997.
Jon M., Kleinberg. Authoritative sources in a hyperlinked environment. J. ACM, 46 (5):604-632, 1999.Google Scholar
D. E., Knuth, J. H., Morris, and V. R., Pratt. Fast pattern matching in strings. SIAM J. Comput., 6(2):323–350, 1977.Google Scholar
Donald E., Knuth. Art of Computer Programming, Volume 3: Sorting and Searching (2nd Edition). Addison-Wesley Professional, 1998.
J. J., Koenderink and A. J., van Doom. Representation of local geometry in the visual system. Biol. Cybern., 55(6):367–375, 1987.Google Scholar
R., Koenen. Mpeg-4 overview (v.16 la bauleversion), iso/iec jtc1/sc29/wg11 n3747, int'l standards organization, oct. 2000.
Teuvo, Kohonen. Self-organized formation of topologically correct feature maps, in Neurocomputing: Foundations of Research, J. A., Anderson and E., Rosenfeld, Eds., MIT Press, Cambridge, MA, pages 509-521, 1988.
Tamara G., Kolda and Brett W., Bader. Tensor decompositions and applications. SIAM Review, 51(3):455–500, September 2009.Google Scholar
Flip, Korn, Nikolaos, Sidiropoulos, Christos Faloutsos, Eliot Siegel, and Zenon Protopapas. Fast nearest neighbor search in medical image databases. In VLDB, pages 215–226, 1996.
Donald, Kossmann, Frank, Ramsak, and Steffen, Rost. Shooting stars in the sky: an online algorithm for skyline queries. In VLDB '02: Proceedings of the 28th International Conference on Very Large Data Bases, pages 275–286, 2002.
R., Kowalski and M., Sergot. A logic-based calculus of events. New Generation Comput., 4(1):67–95, 1986.Google Scholar
Pieter M., Kroonenberg and Jan De, Leeuw. Principal component analysis of three-mode data by means of alternating least squares algorithms. Psychometrika, 1(45):69–97, 1980.Google Scholar
J. B., Kruskal. Nonmetric multidimensional scaling: a numerical method. Psychometrika, 29(2):115–129, 1964a.Google Scholar
Joseph B., Kruskal. Multidimensional scaling by optimizing goodness of fit to a non-metric hypothesis. Psychometrika, 1(29):1–27, 1964b.Google Scholar
J. B., Kruskal and W., Myron. Multidimensional Scaling. Sage Publications, Beverly Hills, CA, 1978.
Ravi, Kumar, Prabhakar, Raghavan, Sridhar, Rajagopalan, and Andrew, Tomkins. Extracting large-scale knowledge bases from the web. In Proceedings of the 25th VLDB Conference, pages 639–650, 1999.
H. T., Kung, F., Luccio, and F. P., Preparata. On finding the maxima of a set of vectors. J. ACM, 22(4):469–476, 1975.Google Scholar
Tony C. T., Kuo and Arbee L. P., Chen. A content-based query language for video databases. In ICMCS, pages 209–214, 1996.
S., Kurtz. Approximate string searching under weighted edit distance. In Proc. WSP'96, pages 156-170. Carleton University Press, 1996.
John, Lafferty and Chengxiang, Zhai. Document language models, query models, and risk minimization for information retrieval. In SIGIR '01: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 111–119, 2001.
L. V., Lakshmanan, N., Leone, R., Ross, and V. S., Subrahmanian. Probview: A flexible probabilistic database system. ACM Trans. Database Syst., 3(22):419–469, 1997.Google Scholar
G. M., Landau and U., Vishkin. Fast string matching with k differences. J. Comput. Syst. Sci., 37:63–78, 1988.Google Scholar
G. M., Landau and U., Vishkin. Fast parallel and serial approximate string matching. J. Algorithms, 10(2):157–169, 1989.Google Scholar
Christian A., Lang, Yuan-Chi, Chang, and John R., Smith. Making the threshold algorithm access cost aware. IEEE Trans. Knowl. Data Eng., 16(10):1297–1301, 2004.Google Scholar
Soren, Larsen and L.N., Kanal. Analysis of k-nearest neighbor branch and bound rules. Pattern Recogn. Lett., 4(2):71–77, 1986.Google Scholar
O., Lassila and R., Swick. Resource description framework (rdf) model and syntax specification. http://www.w3.org/tr/rec-rdf-syntax., 1999.
Lieven De, Lathauwer, Bart De, Moor, and Joos Van de walle. A multilinearsingular value decomposition. SIAM J. Matrix Anal. A., 21(4):1253–1278, 2000.Google Scholar
J. K., Lawder. The application of space-filling curves to the storage and retrieval of multi-dimensional data. Technical Report JL/1/99, Birkbeck College, University of London, 1999.
Iosif, Lazaridis and Sharad, Mehrotra. Progressive approximate aggregate queries with a multi-resolution tree structure. In SIGMOD '01: Proceedings of the 2001 ACM SIGMOD International Conference on Management of Data, pages 401–412, 2001.
Svetlana, Lazebnik, Cordelia, Schmid, and Jean, Ponce. A sparse texture representation using affine-invariant regions. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2, page 319, 2003.
Anthony J. T., Lee and Han-Pang, Chiu. 2D Z-string: a new spatial knowledge representation for image databases. Pattern Recogn. Lett., 24(16):3015–3026, 2003.Google Scholar
Jeong Ki, Lee and Jae Woo, Chang. Performance evaluation of hybrid access methods for efficient information retrieval. In Proceedings of the 20th EUROMICRO Conference, pages 372–378, 1994.
John A., Lee and Michel, Verleysen. Nonlinear Dimensionality Reduction. Springer, 2007.
S. Y., Lee and F. J., Hsu. Spatial reasoning and knowledge representation. Pattern Recogn., 25(3):305–318, 1992.Google Scholar
S. Y., Lee, M. C., Yang, and J. W., Chen. 2D B-string: a spatial knowledge representation for image database systems. In Second International Computer Science Conference (ICSC), 1992.
Taekyong, Lee, Lei, Sheng, Tolga, Bozkaya, Nevzat Hurkan, Balkir, Meral, Özsoyoglu, and Gultekin, Özsoyoglu. Querying multimedia presentations based on content, IEEE Transactions on Knowledge and Data Engineering, 11(3), pages 361-385, May/Jun 1999, 2001.Google Scholar
Jure, Leskoec, Kevin J., Lang, Anirban, Dasgupta, and Michael W., Mahoney. Statistical properties of community structure in large social and information networks. In WWW '08: Proceeding of the 17th international conference on World Wide Web, pages 695–704, 2008.
Jure, Leskovec and Christos, Faloutsos. Sampling from large graphs. In KDD '06: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 631–636, 2006.
Jure, Leskovec, Jon, Kleinberg, and Christos, Faloutsos. Graph evolution: Densification and shrinking diameters. ACM Trans. Knowl. Discov. Data, 1(1):1–41, 2007.Google Scholar
Scott T., Leutenegger, J. M., Edgington, and Mario A., Lopez. Str: A simple and efficient algorithm for r-tree packing. In ICDE '97: Proceedings of the Thirteenth International Conference on Data Engineering, pages 497–506, 1997.
V. I., Levenshtein. Binary codes capable of correcting deletions, insertions, and reversals. Soviet Phy. Dok., 10:707–710, 1966.Google Scholar
Hector J., Levesque, Fiora, Pirri, and Raymond, Reiter. Foundations for the situation calculus. Electron. Trans. Artif. Intell., 2:159–178, 1998.Google Scholar
A., Levy and M., Lindenbaum. Sequential Karhunen-Loeve basis extraction and its application to images. IEEE Trans. Image Proc., 9:1371–1374, 2000.Google Scholar
Chengkai, Li, Kevin Chen-Chuan Chang, Ihab F. Ilyas, and Sumin Song. RankSQL: query algebra and optimization for relational top-k queries. In SIGMOD '05: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data, pages 131–142, 2005.
Jian, Li and Amol, Deshpande. Consensus answers for queries over probabilistic databases. In PODS '09: Proceedings of the Twenty-eighth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, pages 259–268, 2009.
John Z., Li, M., Tamer, Duane, Szafron, and Vincent, Oria. Moql: A multimedia object query language. In Proceedings of the 3rd International Workshop on Multimedia Information Systems, 1997a.
Lian, Li, Ahmed, Karmouch, and Nicolas D., Georganas. Multimedia teleorchestra with independent sources: Part 1 – temporal modeling of collaborative multimedia scenarios. Multimedia Syst., 1(4):143–153, 1994a.Google Scholar
Lian, Li, Ahmed, Karmouch, and Nicolas D., Georganas. Multimedia teleorchestra with independent sources: Part 2 - synchronization algorithms. Multimedia Syst., 1(4):154–165, 1994b.Google Scholar
Qing, Li, K. Selçuk, Candan, and Qi, Yan. Extracting relevant snippets for web navigation. In Proceedings of the Twenty-third AAAI Conference on Artificial Intelligence (AAAI), pages 1195–1200, 2008.
W.-S., Li and K.S., Candan. Semcog: A hybrid object-based image and video database system and its modeling, language, and query processing. TAPOS, 5(3):163–180, 1999a.Google Scholar
Wen-Syan, Li and K. Selçuk, Candan. Integrating content search with structure analysis for hypermedia retrieval and management. ACM Comput. Surv., 31(4es):13–20, 1999b.Google Scholar
Wen-Syan, Li, K. Selçuk, Candan, Kyoji, Hirata, and Yoshinori, Hara. Facilitating multimedia database exploration through visual interfaces and perpetual query reformulations. In VLDB, pages 538–547, 1997b.
Wen-Syan, Li, K. Selçuk, Candan, Kyoji, Hirata, and Yoshinori, Hara. Ifq: A visual query interface and query generator for object-based media retrieval. In ICMCS, pages 353–361, 1997c.
Wen-Syan, Li, K. Selçuk, Candan, Quoc, Vu, and Divyakant, Agrawal. Retrieving and organizing web pages by information unit. In WWW, pages 230–244, 2001a.
Wen-Syan, Li, K. Selçuk, Candan, Kyoji, Hirata, and Yoshinori, Hara. Supporting efficient multimedia database exploration. VLDB J., 9(4):312–326, 2001b.Google Scholar
Wentian, Li. Random texts exhibit Zipf's law-like word frequency distribution. IEEE Trans. Inform. Theory, 38, 1992.Google Scholar
Z. N., Li and M. S., Drew. Fundamentals of Multimedia. Prentice-Hall, 2003.
King Ip, Lin, H. V., Jagadish, and Christos, Faloutsos. The TV-tree: an index structure for high-dimensional data. VLDB J., 3(4):517–542, 1994.Google Scholar
Jessica, Lin, Eamonn J., Keogh, Stefano, Lonardi, and Bill Yuan-chi, Chiu. A symbolic representation of time series, with implications for streaming algorithms. pages 211, June 2003.
Ping, Lin and K. Selçuk, Candan. Enabling access-privacy for random walk based data analysis applications. Data Knowl. Eng., 63(3):667–683, 2007.Google Scholar
T. D. C., Little and A., Ghafoor. Interval-based conceptual models for time-dependent multimedia data. IEEE Trans. Knowl. Data Eng., 5(4):551–563, 1993.Google Scholar
Thomas D. C., Little and Arif, Ghafoor. Synchronization and storage models for multimedia objects. IEEE J. Sel. Areas Commun., 8(3):413–427, 1990.Google Scholar
Nick, Littlestone. From on-line to batch learning. In COLT '89: Proceedings of the Second Annual Workshop on Computational Learning Theory, pages 269–284, 1989.
Peiya, Liu, Amit, Chankraborty, and Liang H., Hsu. A predicate logic approach for MPEG-7 XML document queries. Markup Lang., 3(3):365–381, 2001.Google Scholar
Bin, Liu, Amarnath, Gupta, and Ramesh, Jain. Medsman: a streaming data management system over live multimedia. In Multimedia '05: Proceedings of the 13th annual ACM International Conference on Multimedia, pages 171–180, 2005.
Bin, Liu, Amarnath, Gupta, and Ramesh, Jain. Medsman: a live multimedia stream querying system. Multimedia Tools Appl., 38(2):209–232, 2008.Google Scholar
S., Lloyd. Least squares quantization in pcm. IEEE Trans. Inform. Theory, 28(2): 129-137, 1982.Google Scholar
S. P., Lloyd. Least squares quantization in PCM'S. Bell Tele. Labs Memo, 1957.
Daniel P., Lopresti and Gordon T., Wilfong. Comparing semi-structured documents via graph probing. In Multimedia Information Systems, pages 41–50, 2001.
D. G., Lowe. Three-dimensional object recognition from single two-dimensional images. Artif. Intell., 31(3):355–395, 1987.Google Scholar
David G., Lowe. Object recognition from local scale-invariant features. In ICCV '99: Proceedings of the International Conference on Computer Vision, Volume 2, pages 1150-1157, 1999.
David G., Lowe. Distinctive image features from scale-invariant keypoints. Int. J. Comp. Vision, 60:91–110, 2004.Google Scholar
F., Luccio and L., Pagli. Approximate matching for two families of trees. Inform. Comput., 123(1):111–120, 1995.Google Scholar
H. P., Luhn. A statistical approach to mechanized encoding and searching of literary information. IBM J. Res. Dev., 1(4):309–317, 1957.Google Scholar
F., Lumbreras and J., Serrat. Wavelet filtering for the segmentation of marble images. Opt Eng, 35(10):2864–2872, October 1996.Google Scholar
Lakshmi Priya, Mahalingam and K. Selçuk, Candan. Multi-criteria query optimization in the presence of result size and quality tradeoffs. Multimedia Tools Appl., 23(3):167–183, 2004.Google Scholar
Michael W., Mahoney, Mauro, Maggioni, and Petros, Drineas. Tensor-cur decompositions for tensor-based data. In KDD '06: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 327–336, 2006.
D., Maier. Comments on the “third-generation database system manifesto.” Oregon Graduate Institute Working Paper, 1991.
Nikos, Mamoulis, Kit Hung, Cheng, Man Lung, Yiu, and David W., Cheung. Efficient aggregation of ranked inputs. In ICDE '06: Proceedings of the 22nd International Conference on Data Engineering, page 72, 2006.
Udi, Manber. Finding similar files in a large file system. In Proceedings of the USENIX Winter 1994 Technical Conference, pages 1–10, 1994.
Udi, Manber and Eugene W., Myers. Suffix arrays: a new method for on-line string searches. SIAM J. Comput., 22(5):935–948, 1993.Google Scholar
Christopher D., Manning and Hinrich, Schtze. Foundations of Statistical Natural Language Processing. MIT Press, 1999.
J., Mao and A. K., Jain. Texture classification and segmentation using multiresolution simultaneous autoregressive models. Pattern Recogn., 25(2):173–188, 1992.Google Scholar
Sherry, Marcus and V. S., Subrahmanian. Foundations of multimedia database systems. J. ACM, 43(3):474–523, 1996.Google Scholar
Amélie, Marian, Nicolas, Bruno, and Luis, Gravano. Evaluating top-k queries over web-accessible databases. ACM Trans. Database Syst., 29(2):319–362, 2004.Google Scholar
Jose L., Marroquin and Federico, Girosi. Some extensions of the k-means algorithm for image segmentation and pattern classification. Technical report, Cambridge, MA, USA, 1993.
Andre T., Martins. String kernels and similarity measures for information retrieval. Technical report, Priberam, Lisbon, Portugal, 2006.
C.B., Mayer, K.S., Candan, and V., Sangam. Effects of user request patterns on a multimedia delivery system. Multimedia Tools Appl., 24(3):233–251, 2004.Google Scholar
S., McAdams and A., Bregman. Hearing musical streams. Comp. Music J., 3(4):26–43, 1979.Google Scholar
Edward M., McCreight. A space-economical suffix tree construction algorithm. J. ACM, 22(2):262–272, 1976.Google Scholar
G. J., McLachlan and K. E., Basford. Mixture Models: Inference and Applications to Clustering. Marcel Dekker, New York, 1988.
F., McSherry. Spectral partitioning of random graphs. In FOCS '01: Proceedings of the 42nd IEEE Symposium on Foundations of Computer Science, page 529, 2001.
Christoph, Meinel and Thorsten, Theobald. Algorithms and Data Structures in VLSI Design. Springer-VerlagNew York, 1998.
Jim, Melton and Andrew, Eisenberg. SQL multimedia and application packages (SQL/MM). SIGMOD Ree, 30(4):97–102, 2001.Google Scholar
María Luisa, Micó, José, Oncina, and Enrique, Vidal. A new version of the nearest-neighbour approximating and eliminating search algorithm (AESA) with linear preprocessing time and memory requirements. Pattern Recogn. Lett., 15(1):9–17, 1994.Google Scholar
María Luisa, Micó, Jose, Oncina, and Rafael C., Carrasco. A fast branch & bound nearest neighbour classifier in metric spaces. Pattern Recogn. Lett., 17:731–739, 1996.Google Scholar
K., Mikolajczyk and C., Schmid. A performance evaluation of local descriptors. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2, pages 257-263, 2003.
Krystian, Mikolajczyk and Cordelia, Schmid. A performance evaluation of local descriptors. IEEE Trans. Pattern Anal. Mach. Intell., 27(10):1615–1630, 2005.Google Scholar
David R., Miller, Tim, Leek, and Richard M., Schwartz. A hidden Markov model information retrieval system. In Proceedings of SIGIR-99, 22nd ACM International Conference on Research and Development in Information Retrieval, pages 214–221, 1999.
I., Mirbel, B., Pernici, and M., Vazirgiannis. Temporal integrity constraints in interactive multimedia documents. In ICMCS '99: Proceedings of the IEEE International Conference on Multimedia Computing and Systems, Volume 2, page 867. IEEE Computer Society, 1999.
Mandar, Mitra, Amit, Singhal, and Chris, Buckley. Improving automatic query expansion. In SIGIR '98: Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 206–214, 1998.
Mohamed F., Mokbel, Ming, Lu, and Walid G., Aref. Hash-merge join: a non-blocking join algorithm for producing fast and early join results. In ICDE, pages 251-263, 2004.
C. L., Monma and J. B., Sidney. Sequencing with series-parallel precedence constraints. Mathematics of Operations Research, 1979.
Ugo, Montanari. On the optimal detection of curves in noisy pictures. Commun. ACM, 14(5):335–345, 1971.Google Scholar
J. W., Moon and L., Moser. On cliques in graphs. Israel J. Math., 3:23-28, 1965.Google Scholar
Raymond J., Mooney and Loriene, Roy. Content-based book recommending using learning for text categorization. In DL '00: Proceedings of the Fifth ACM Conference on Digital Libraries, pages 195–204, New York, NY, USA, 2000.
Donald R., Morrison. Patricia – practical algorithm to retrieve information coded in alphanumeric. J. ACM, 15(4):514–534, 1968.Google Scholar
G.M., Morton. A computer oriented geodetic data base; and a new technique in file sequencing. Technical Report, Ottawa, Canada: IBM Ltd., 1966.
S., Muthukrishnan and H., Ramesh. String matching under a general matching relation. Inform. Comput., 122(1):140–148, 1995.Google Scholar
G., Myers. Incremental alignment algorithms and their applications. tr-8622. Technical report, Deptartment of Computer Science, University of Arizona, 1986.
Mohammad, Nabil, Anne H. H., Ngu, and John, Shepherd. Picture similarity retrieval using the 2D projection interval representation. IEEE Trans. Knowl. Data Eng., 08(4):533–539, 1996.Google Scholar
Klara, Nahrstedt and Wolf-Tilo, Balke. A taxonomy for multimedia service composition. In Multimedia '04: Proceedings of the 12th ACM International Conference on Multimedia, pages 88–95, 2004.
Atsuyoshi, Nakamura and Naoki, Abe. Collaborative filtering using weighted majority prediction algorithms. In ICML '98: Proceedings of the Fifteenth International Conference on Machine Learning, pages 395–403, San Francisco, CA, USA, 1998. Morgan Kaufmann.
Nathan Srebro, Nati and Tommi, Jaakkola. Weighted low-rank approximations. In 20th International Conference on Machine Learning, pages 720-727. AAAI Press, 2003.
Apostol, Natsev, Yuan chi, Chang, John R., Smith, Chung-Sheng, Li, and Jeffrey Scott, Vitter. Supporting incremental join queries on ranked inputs. In VLDB, pages 281-290, 2001.
D., Nauck and R., Kruse. Obtaing interpretable fuzzy classification rules from medical data. Artif. Intell. Med., pages 149–169, 1999.
G., Navarro and M., Raffinot. A bit-parallel approach to suffix automata: fast extended string matching. In Proceedings of the 9th Annual Symposium on Combinatorial Pattern Matching, pages 14–33, 1998.
Gonzalo, Navarro. Multiple approximate string matching by counting. In Proceedings of WSP'97, pages 125-139. Carleton University Press, 1997.
Gonzalo, Navarro. A guided tour to approximate string matching. ACM Comput. Surv., 33(1):31–88, 2001.Google Scholar
Gonzalo, Navarro. Searching in metric spaces by spatial approximation. VLDB J., 11(1):28–46, 2002.Google Scholar
Gonzalo, Navarro. Searching in metric spaces by spatial approximation. In SPIRE '99: Proceedings of the String Processing and Information Retrieval Symposium & International Workshop on Groupware, page 141, 1999.
Surya, Nepal and M. V., Ramakrishna. Query processing issues in image (multimedia) databases. In ICDE '99: Proceedings of the 15th International Conference on Data Engineering, pages 22–29, 1999.
M. E. J., Newman and M., Girvan. Finding and evaluating community structure in networks. Phys. Rev. E, 69(2), 2004.Google Scholar
Hieu Tat, Nguyen, Marcel, Worring, and Rein, van den Boomgaard. Watersnakes: energy-driven watershed segmentation. IEEE Trans. Pattern Anal. Mach. Intell., 25(3):330–342, 2003.Google Scholar
Carlton W., Niblack, Ron, Barber, Will, Equitz, Myron D., Flickner, Eduardo H., Glasman, Dragutin, Petkovic, Peter, Yanker, Christos, Faloutsos, and Gabriel, Taubin. Qbic project: querying images by content, using color, texture, and shape. Proc. SPIE, 1908 (173): 1-10, 1993.Google Scholar
Andrew, Nierman and H. V., Jagadish. Evaluating structural similarity in XML documents. In WebDB, pages 61–66, 2002.
Jürg, Nievergelt, Hans, Hinterberger, and Kenneth C., Sevcik. The grid file: an adaptable, symmetric multi-key file structure. In Proceedings of the 3rd Conference of the European Cooperation in Informatics on Trends in Information Processing Systems, pages 236–251, 1981.
Haruhiko, Nishiyama, Sumi, Kin, Teruo, Yokoyama, and Yutaka, Matsushita. An image retrieval system considering subjective perception. In ACM SIGCHI '94: Conference Companion on Human Factors in Computing Systems, page 201, 1994.
Albert B., Novikoff. On convergence proofs for perceptrons. In Proceedings of the Symposium on the Mathematical Theory of Automata, Volume 12, pages 615-622, 1963.
G., O'Brien. Information management tools for updating an SVD-encoded indexing scheme, Master's Thesis, The University of Konxville, Tennessee, 1994.
Virginia E., Ogle and Michael, Stonebraker. Chabot: retrieval from a relational database of images. Computer, 28(9):40–48, 1995.Google Scholar
Dan, Olteanu and Jiewen, Huang. Secondary-storage confidence computation for conjunctive queries with inequalities. In SIGMOD '09: Proceedings of the 35th SIGMOD International Conference on Management of Data, pages 389–402, 2009.
Beng Chin, Ooi, Kian-Lee, Tan, Cui, Yu, and Stéphane Bressan. Indexing the edges–a simple and yet efficient approach to high-dimensional indexing. In Proceedings of the Principles ofDatabase Systems, pages 166–174, 2000.
Eitetsu, Oomoto and Katsumi, Tanaka. Ovid: design and implementation of a video-object database system. IEEE Trans. Knowl. Data Eng., 5(4):629–643, 1993.Google Scholar
M. T., Orchard. A fast nearest-neighbor search algorithm. In IEEE International Conference on Acoustics. Speech, and Signal Processing, Volume 4, pages 2297–2300, 1991.
J. A., Orenstein. Redundancy in spatial databases. SIGMOD Rec., 18(2):295–305, 1989.Google Scholar
Vincent, Oria, M. Tamer, Ozsu, Bing, Xu, L. Irene, Cheng, and Paul J., Iglinski. Vi-sualmoql: The disima visual query language. ICMCS, 01:9536, 1999.Google Scholar
Gultekin, Özsoyoĝlu, Veli, Hakkoymaz, and Joel, Kraft. Automating the assembly of presentations from multimedia databases. In ICDE '96: Proceedings of the Twelfth International Conference on Data Engineering, pages 593-601. IEEE Computer Society, 1996.
Lawrence, Page, Sergey, Brin, Rajeev Motwani, and Terry Winograd. The pagerank citation ranking: Bringing order to the web. Technical report, Stanford Digital Library Technologies Project, 1998.
Dimitris, Papadias, Yufei, Tao, Greg, Fu, and Bernhard, Seeger. Progressive skyline computation in database systems. ACM Trans. Database Syst., 30(1):41–82, 2005.Google Scholar
Christos H., Papadimitriou and Mihalis, Yannakakis. Multi objective query optimization. In PODS '01: Proceedings of the Twentieth ACM SIGMOD-SIGACT-SIGART Symposium on Principles ofDatabase Systems, pages 52–59, 2001.
Spiros, Papadimitriou, Jimeng, Sun, and Christos, Faloutsos. Streaming pattern discovery in multiple time-series. In VLDB '05: Proceedings of the 31st International Conference on Very Large Data Bases, pages 697–708, 2005.
Apostolos N., Papadopoulos and Yannis, Manolopoulos. Structure-based similarity search with graph histograms. In DEXA '99: Proceedings of the 10th International Workshop on Database & Expert Systems Applications, page 174, 1999.
Y., Papakonstantinou, H., Garcia-Molina, and J., Widom. Object exchange across heterogeneous information sources. Proceedings of the Eleventh International Conference on Data Engineering, 1995, pages 251–260, March 1995.
Panos M., Pardalos and Stephen A., Vavasis. Quadratic programming with one negative eigenvalue is NP-hard. J. Global Optim., 1(1):15–22, 1991.Google Scholar
Dong Kwon, Park, Yoon Seok, Jeon, and Chee Sun, Won. Efficient use of local edge histogram descriptor. In MULTIMEDIA '00: Proceedings of the 2000 ACM Workshops on Multimedia, pages 51–54, 2000.
T., Pavlidis and Y.-T., Liow. Integrating region growing and edge detection. IEEE Trans. Pattern Anal. Mach. Intell., 12(3):225–233, 1990.Google Scholar
Manoj M., Pawar, Gaurav N., Pradhan, Kang, Zhang, and Balakrishnan, Prabhakaran. Content based querying and searching for 3d human motions. In MMM, pages 446-455, 2008.
Giuseppe, Peano. Sur une courbe, qui remplit toute une aire plane (on a curve which completely fills a planar region). Math. Ann., 36:157–160, 1890.Google Scholar
J., Pearl. Bayesian networks: a model of self-activated memory for evidential reasoning. In Proceedings of the Conference of the Cognitive Science Society, pages 329-334, 1985.
Dan, Pelleg. X-means: Extending k-means with efficient estimation of the number of clusters. In Proceedings of the 17th International Conference on Machine Learning, pages 727–734, 2000.
Lina, Peng and K. Selçuk, Candan. Data-quality guided load shedding for expensive in-network data processing. In ICDE, pages 1325–1328, 2007.
Lina, Peng, Gisik, Kwon, Yinpeng, Chen, K. Selçuk, Candan, Hari, Sundaram, Karam S., Chatha, and Maria Luisa, Sapino. Modular design of media retrieval workflows using aria. In CIVR, pages 491–494, 2006.
Lina, Peng, K. Selçuk, Candan, Christopher, Mayer, Karamvir S., Chatha, and Kyung Dong, Ryu. Optimization of media processing workflows with adaptive operator behaviors. Multimedia Tools Appl., 33(3), 2007.Google Scholar
Lina, Peng, Renwei, Yu, K. Selçuk, Candan, and Xinxin, Wang. Object and combination shedding schemes for adaptive media workflow execution. IEEE Trans. Knowl. Data Eng., 22(1), pages 105-119, 2010.Google Scholar
David, Pennock, Eric, Horvitz, Steve, Lawrence, and C Lee, Giles. Collaborative filtering by personality diagnosis: a hybrid memory- and model-based approach. In Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence, pages 473–480, 2000.
Haim, Permuter, Joseph, Francos, and Ian, Jermyn. A study of gaussian mixture models of color and texture features for image classification and segmentation. Pattern Recogn., 39(4):695–706, 2006.Google Scholar
E., Persoon and K. S., Fu. Shape discrimination using fourier descriptors. IEEE Trans. Pattern Anal. Mach. Intell., 8(3):388–397, 1986.Google Scholar
G., Petraglia, M., Sebillo, M., Tucci, and G., Tortora. Virtual images for similarity retrieval in image databases. IEEE Trans. Knowl. Data Eng., 13(6):951–967, Nov/Dec 2001.Google Scholar
G., Piatetsky-Shapiro. Discovery, Analysis, and Presentation of Strong Rules, pages 229-248. AAAI/MIT Press, 1991.
Claudio, Pinhanez and Aaron, Bobick. Fast constraint propagation on specialized Allen networks and its application to action recognition and control [electronic version]. Technical report, MIT Media Lab Perceptual Computing Section, 1998.
Claudio S., Pinhanez, Kenji, Mase, and Aaron, Bobick. Interval scripts: a design paradigm for story-based interactive systems. In CHI '97: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 287-294. ACM, 1997.
Jay M., Ponte and W. Bruce, Croft. A language modeling approach to information retrieval. In SIGIR '98: Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 275–281, 1998.
Alex, Pothen, Horst D., Simon, and Kan-Pu, Liou. Partitioning sparse matrices with eigenvectors of graphs. SIAMJ. Matrix Anal. Appl., 11(3):430–452, 1990.Google Scholar
B., Prabhakaran and S. V., Raghavan. Synchronization models for multimedia presentation with user participation. Multimedia Syst., 2(2):53–62, 1994.Google Scholar
Franco P., Preparata and Michael I., Shamos. Computational Geometry: An Introduction (Monographs in Computer Science). Springer, 1985.
William H., Press, Brian P., Flannery, Saul A., Teukolsky, and William T., Vetterling. Numerical Recipes in C: the Art of Scientific Computing. Cambridge University Press, New York, 1988.
Foster J., Provost, Tom, Fawcett, and Ron, Kohavi. The case against accuracy estimation for comparing induction algorithms. In ICML '98: Proceedings of the Fifteenth International Conference on Machine Learning, pages 445–453, 1998.
H., Prüfer. Neuer Beweis eines Satzes über Permutationen. Archiv fur Mathematik und Physik, 27:142–144, 1918.Google Scholar
P., Punitha and D. S., Guru. An effective and efficient exact match retrieval scheme for symbolic image database systems based on spatial reasoning: a logarithmic search time approach. IEEE Trans. Knowl. Data Eng., 18(10):1368–1381, 2006.Google Scholar
Yan, Qi, K. Selçuk, Candan, and Maria Luisa, Sapino. Sum-max monotonic ranked joins for evaluating top-k twig queries on weighted data graphs. In VLDB, pages 507-518, 2007.
J. R., Quinlan. Rulequest research: See5/c5.0_2.05. http://www.rulequest.com/, 2008.
J. R., Quinlan. Improved use of continuous attributes in C4.5. J. Artif. Intell. Res., 4: 77-90, 1996.Google Scholar
J. Ross, Quinlan. C4.5: Machine Learning. Morgan Kaufmann, 1993.
J. Ross, Quinlan. Machine Learning, Volume 1. 1975.
Lawrence R., Rabiner. A tutorial on hidden Markov models and selected applications in speech recognition, Proceedings of the IEEE, 77(2), pages 267-296, 1990.
R., Rada, H., Mili, E., Bicknell, and M., Blettner. Development and application of a metric on semantic nets. IEEE Trans. Syst. Man Cybernet., 19(1):17–30, 1989.Google Scholar
Davood, Rafiei, Daniel L., Moise, and Dabo, Sun. Finding syntactic similarities between XML documents. In DEXA '06: Proceedings of the 17th International Conference on Database and Expert Systems Applications, pages 512-516. IEEE Computer Society, 2006.
Adrian E., Raftery. Choosing models for cross-classifications. Am. Sociol. Rev., 51 (1):145-146, February 1986.Google Scholar
A. E., Raftery. Bayes factors and BIC-comment on “a critique of the Bayesian information criterion for model selection.”Sociol. Methods Res., 27:411–427, 1999.Google Scholar
Praveen, Rao and Bongki, Moon. Prix: Indexing and querying XML using Prüfer sequences. In ICDE '04: Proceedings of the 20th International Conference on Data Engineering, page 288, 2004.
Christopher, Re, Nilesh N., Dalvi, and Dan, Suciu. Query evaluation on probabilistic databases. IEEE Data Eng. Bull., 29(1):25–31, 2006.Google Scholar
G., Reich and P., Widmayer. Approximate minimum spanning trees for vertex classes. Technical Report, Institut für Informatik, Freiburg University, 1991.
P., Resnick, N., Iacovou, M., Suchak, P., Bergstorm, and J., Riedl. Grouplens: an open architecture for collaborative filtering of netnews. In Proceedings of ACM 1994 Conference on Computer Supported Cooperative Work, pages 175–186, 1994.
R., Richardson and A., Smeaton. Using wordnet in a knowledge-based approach to information retrieval. In BCS-IRSG Colloquium on Information Retrieval, 1995.
J., Rissanen. Modelling by the shortest data description. Automatica, 14:465–471, 1978.Google Scholar
Stephen J., Roberts, Dirk, Husmeier, William, Penny, and lead, Rezek. Bayesian approaches to gaussian mixture modeling. IEEE Trans. Pattern Anal. Mach. Intell., 20(11):1133–1142, 1998.Google Scholar
S. E., Robertson. On term selection for query expansion. J. Documentation, 46(4): 359-364, December 1990.Google Scholar
S. E., Robertson and Sparck K., Jones. Relevance weighting of search terms. J. Am. Soc. Inform. Sci., 27(3):129–146, 1976.Google Scholar
S. E., Robertson and K. Karen, Spark-Jones. Relevance weighting of search terms. J. Am. Soc. Inform. Sci., 27(3):129–146, 1976.Google Scholar
Stephen E., Robertson and Karen Sparck, Jones. Relevance weighting of search terms, in Document Retrieval Systems, P., Willett, Ed. Taylor Graham Series In Foundations Of Information Science, vol. 3, Taylor Graham Publishing, London, UK, pages 143-160, 1988.
John T., Robinson. The k-d-b-tree: a search structure for large multidimensional dynamic indexes. In SIGMOD '81: Proceedings of the 1981 ACM SIGMOD International Conference on Management of Data, pages 10–18, 1981.
J. J., Rocchio. Relevance Feedback in Information Retrieval, chapter 14, in The Smart Retrieval System – Experiments in Automatic Document Processing, Prentice-Hall, pages 313-323, 1971.
Jos B. T. M., Roerdink and Arnold, Meijster. The watershed transform: definitions, algorithms and parallelization strategies. Fundam. Inform., 41(1-2):187-228, 2000.Google Scholar
Frank, Rosenblatt. The perceptron: a probabilistic model for information storage and organization in the brain. Psychol. Rev., 65(6):386–408, November 1958.Google Scholar
A., RosenfeldR. B., Thomas, and Y. H., Lee. Edge and curve enhancement in digital pictures. Tech. Rep. 69-93. Technical Report, University of Maryland, College Park, 1969.
R., Rosenfeld. Two decades of statistical language modeling: where do we go from here?Proc. IEEE, 88(8):1270–1278, 2000.Google Scholar
Johannes A., Roubos, Magne, Setnes, and János, Abonyi. Learning fuzzy classification rules from labeled data. Inform. Sci., 150(1-2):77-93, 2003.Google Scholar
Nick, Roussopoulos and Daniel, Leifker. Direct spatial search on pictorial databases using packed R-trees. SIGMOD Rec., 14(4):17–31, 1985.Google Scholar
Nick, Roussopoulos, Stephen, Kelley, and Frederic, Vincent. Nearest neighbor queries. In ACM SIGMOD, pages 71–79, 1995.
R., Rudzkis and M., Radavicius. Statistical estimation of a mixture of gaussian distributions. Acta Applicandae Mathematicae, 38:37–54, 1995.Google Scholar
Y., Rui and T. S., Huang. Relevance feedback techniques in image retrieval. In M.S., Lew, editor, Principles of Visual Information Retrieval, pages 219-258. SpringerVerlag, 2001.
Richard, Russell and Pawan, Sinha. Perceptually-based comparison of image similarity metrics. MIT Technical Report, AIM-2001-014, CBCL-201, 2001.
Stuart, Russell and Peter, Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, 1995.
I., Ruthven, M., Lalmas, and C. J., van Rijsbergen. Ranking expansion terms using partial and ostensive evidence. In Proceedings of the 4th International Conference on Conceptions of Library and Information Science. CoLIS 4, pages 199–220, 2002.
Ian, Ruthven and Mounia, Lalmas. A survey on the use of relevance feedback for information access systems. Knowl. Eng. Rev., 18(2):95–145, June 2003.Google Scholar
S. K., Chang, E., Jungert, and Y., Li. Representation and retrieval of symbolic pictures using generalized 2-D strings. In Proc. SPIE: Visual Communication Image Process, IV, pages 1360–1372, 1989.
R., Sacks-Davis, A., Kent, and K., Ramamohanarao. Multikey access methods based on superimposed coding techniques. ACM Trans. Database Syst., 12(4):655–696, 1987.Google Scholar
Ron, Sacks-Davis. Performance of a multi-key access method based on descriptors and superimposed coding techniques. Inform. Syst., 10(4):391–403, 1985.Google Scholar
Ron, Sacks-Davis, Alan, Kent, Kotagiri Ramamohanarao, James Thom, and Justin Zobel. Atlas: A nested relational database system for text applications. IEEE Trans. Knowl. Data Eng., 7(3):454–470, 1995.Google Scholar
J. A., Saghri and H., Freeman. Analysis of the precision of generalized chain codes for the representation of planar curves. PAMI, 3(5):533–539, September 1981.Google Scholar
Mukesh K., Saini, Vivek K., Singh, Ramesh C., Jain, and Mohan S., Kankanhalli. Multimodal observation systems. In MM '08: Proceeding of the 16th ACM international conference on Multimedia, pages 933–936, 2008.
P., Saint-Marc, H., Rom, and G., Medioni. B-spline contour representation and symmetry detection. IEEE Trans. Pattern Anal. Mach. Intell., 15(11):1191–1197, 1993.Google Scholar
Hiroaki, Sakoe. Dynamic programming algorithm optimization for spoken word recognition. IEEE Trans. Acoust, Speech, Signal Proc., 26:43–49, 1978.Google Scholar
G., Salton and C., Buckley. On the use of spreading activation methods in automatic information retrieval. In SIGIR '88: Proceedings of the 11th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 147–160, 1988a.
Gerard, Salton and Chris, Buckley. Term weighting approaches in automatic text retrieval. Inform. Proc. Management, 24:513–523, 1988b.Google Scholar
Gerard, Salton and Chris, Buckley. Improving retrieval performance by relevance feedback. J. Am. Soc. Inform. Sci., 41(4):288–297, 1990.Google Scholar
G., Salton, A., Wong, and C. S., Yang. A vector space model for automatic indexing. Commun. ACM, 18(11):613–620, November 1975.Google Scholar
H., Samet. Neighbor finding in quadtrees. In PRIP'81, pages 68–74, 1981.
H., Samet and C.A., Shaffer. A model for the analysis of neighbor finding in pointer based quadtrees. PAMI, 7(6):717–720, November 1985.Google Scholar
Hanan, Samet. Foundations of Multidimensional and Metric Data Structures. Morgan Kaufmann, San Francisco, CA, USA, 2005.
Hanan, Samet. Applications of Spatial Data Structures: Computer Graphics, Image Processing, and GIS. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 1990.
Hanan, Samet. The quadtree and related hierarchical data structures. ACMComput. Surv., 16(2):187–260, 1984.Google Scholar
M. L., Sapino, K. S., Candan, and P., Bertolotti. Log-analysis based characterization of multimedia documents for effective delivery of distributed multimedia presentations. In Proc. DMS 06, 2006.
Anish Das, Sarma, Omar, Benjelloun, Alon, Halevy, and Jennifer, Widom. Working models for uncertain data. In ICDE '06: Proceedings of the 22nd International Conference on Data Engineering, 2006.
Badrul, Sarwar, George, Karypis, Joseph, Konstan, and John, Riedl. Analysis of recommendation algorithms for e-commerce. In Proceedings of the ACM EC'00 Conference, pages 158–167, 2000.
Badrul, Sarwar, George, Karypis, Joseph, Konstan, and John, Reidl. Item-based collaborative filtering recommendation algorithms. In WWW '01: Proceedings of the 10th International Conference on World Wide Web, pages 285–295, 2001.
Lawrence, Saul and O, Pereira. Aggregate and mixed-order Markov models for statistical language processing. In Proceedings of the Second Conference on Empirical Methods in Natural Language Processing, pages 81–89, 1997.
Satu Elisa, Schaeffer. Graph clustering. Comp. Sci. Rev., 1(1):27–64, 2007.Google Scholar
Frederik, Schaffalitzky and Andrew, Zisserman. Multi-view matching for unordered image sets, or “How do I organize my holiday snaps?” In ECCV '02: Proceedings of the 7th European Conference on Computer Vision – Part I, pages 414–431, 2002.
Cullen, Schaffer. Overfitting avoidance as bias. Mach. Learn., 10(2):153–178, 1993.Google Scholar
Robert E., Schapire and Yoram, Singer. Improved boosting algorithms using confidence-rated predictions. Mach. Learn., 37(3):297–336, 1999.Google Scholar
Ansgar, Scher, Ramesh, Jain, and Mohan, Kankanhalli. Events in multimedia. In MM '09: Proceedings of the 17th ACM International Conference on Multimedia, pages 1147-1148, 2009.
Saul, Schleimer, Daniel S., Wilkerson, and Alex, Aiken. Winnowing: local algorithms for document fingerprinting. In SIGMOD '03: Proceedings of the 2003 ACM SIG-MOD International Conference on Management of Data, pages 76–85, 2003.
Ingo, Schmitt, Nadine, Schulz, and Thomas, Herstel. Ws-qbe: A QBE-like query language for complex multimedia queries. In MMM '05: Proceedings of the 11th International Multimedia Modelling Conference, pages 222-229. IEEE Computer Society, 2005.
P. H., Schoenemann and R., Carroll. Fitting one matrix to another under choice of a central dilation and a rigid motion. Psychometrika, 35(2):245–255, 1970.Google Scholar
Bernhard, Schölkopf, Alexander, Smola, and Klaus-Robert, Müller. Nonlinear component analysis as a kernel eigenvalue problem. Neural Comput., 10(5):1299-1319, 1998.Google Scholar
Peter, Schönemann. A generalized solution of the orthogonal Procrustes problem. Psychometrika, 31(1):1–10, 1966.Google Scholar
Eddie, Schwalb and Rina, Dechter. Processing disjunctions in temporal constraint networks. Artif. Intell., 93(1-2):29-61, 1997.Google Scholar
Gideon, Schwarz. Estimating the dimension of a model. Ann. Statist., 6(2):461–464, 1978.Google Scholar
E. Di, Sciascio, M., Mongiello, F. M., Donini, and L., Allegretti. Retrieval by spatial similarity: an algorithm and a comparative evaluation. Pattern Recogn. Lett., 25 (14):1633-1645, 2004.Google Scholar
Thomas, Seidl and Hans-Peter, Kriegel. Optimal multi-step k-nearest neighbor search. In SIGMOD Conference, pages 154–165, 1998.
A., Seley and B. A., Hanson. Improved 1-bark bandwidth auditory filter. J. Acoust. Soc. Am., 75(6):1902–1904, 1987.Google Scholar
S., Selkow. The Tree-to-tree Editing Problem. Inform. Proc. Lett., 6(6):184–186, 1977.Google Scholar
P., Sellers. The theory and computation of evolutionary distances: pattern recognition. J. Algorithms, 1:359–373, 1980.Google Scholar
Timos K., Sellis, Nick, Roussopoulos, and Christos, Faloutsos. The RH-tree: a dynamic index for multi-dimensional objects. In VLDB '87: Proceedings of the 13th International Conference on Very Large Data Bases, pages 507–518, 1987.
J., Sethuraman. A constructive definition of dirichlet priors. Statist. Sin., 4:639–650, 1994.Google Scholar
M., Setnes and J. A., Roubos. Transparent fuzzy modelling using fuzzy clustering and GA's. In Proceedings ofNAFIPS, pages 198–202, 2000.
Michael Ian, Shamos and Dan, Hoey. Geometric intersection problems. 17th Annual Symposium on Foundations of Computer Science, pages 208–215, 1976.
Claude E., Shannon. Prediction and entropy of printed English. Bell Syst. Tech. J., 30:50–64, 1950.Google Scholar
Marvin, Shapiro. The choice of reference points in best-match file searching. Commun. ACM, 20(5):339–343, 1977.Google Scholar
Vladimir, Shapiro. Accuracy of the straight line Hough transform: the non-voting approach. Comput. Vis. Image Underst., 103(1):1–21, 2006.Google Scholar
Upendra, Shardanand and Pattie, Maes. Social information filtering: algorithms for automating “word of mouth.” In CHI '95: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 210–217, 1995.
M., Sharir. Almost tight upper bounds for lower envelopes in higher dimensions. Discrete Comput. Geom., 12:327–345, 1994.Google Scholar
D., Shasha and K., Zhang. Fast algorithms for the unit cost distance between trees. J. Algorithms, 11:581–621, 1990.Google Scholar
D., Shasha and K., Zhang. Approximate tree pattern matching. In Pattern Matching in Strings, Trees and Arrays, Chapter 14. 1995.
D., Shasha, J. T.-L., Wang, Kaizhong Zhang, and F. Y. Shih. Exact and approximate algorithms for unordered tree matching. IEEE Trans. Syst. Man Cybernet., 24(4): 668-678, 1994.Google Scholar
Dennis, Shasha, Jason, Wang, and Kaizhong, Zhang. Unordered tree comparison based on cousin distance (http://cs.nyu.edu/shasha/papers/cousins.html), downloaded, 2009.
R., Shepard. Circularity in judgements of relative pitch. J. Acoust. Soc. Am., 36:2346–2353, 1964.Google Scholar
A. Prasad, Sistla, Clement T., Yu, and R., Haddad. Reasoning about spatial relationships in picture retrieval systems. In VLDB '94: Proceedings of the 20th International Conference on Very Large Data Bases, pages 570–581, San Francisco, CA, USA, 1994. Morgan Kaufmann.
A. Prasad, Sistla, Clement T., Yu, Chengwen, Liu, and King, Liu. Similarity based retrieval of pictures using indices on spatial relationships. In VLDB '95: Proceedings of the 21th International Conference on Very Large Data Bases, pages 619–629, San Francisco, CA, USA, 1995. Morgan Kaufmann.
John R., Smith and Shih-Fu, Chang. Visualseek: a fully automated content-based image query system. In MULTIMEDIA '96: Proceedings of the Fourth ACM International Conference on Multimedia, pages 87-98. ACM, 1996.
I., Sobel and G., Feldman. A3 × 3 isotropic gradient operator for image processing. Presented as a talk at the Stanford Artificial Project, 1968.
Ian, Soboroff and Charles, Nicholas. Collaborative filtering and the generalized vector space model. In SIGIR '00: Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 351-353, 2000.
Junehwa, Song, Yurdaer N., Doganata, Michelle Y., Kim, and Asser N., Tantawi. Modeling timed user-interactions in multimedia documents. ICMCS, 00, 1996.
Yuqing, Song, Markus, Mielke, and Aidong Zhang. Netmedia: synchronized streaming of multimedia presentations in distributed environments. ICMCS, 585-590, 1999.
Cees, Snoek and Marcel, Worring. Multimedia event-based video indexing using time intervals. IEEE Transactions on Multimedia, 7(4):638–647, 2005.Google Scholar
C., Spearman. The proof and measurement of association between two things. Am. j. Psychol., 15(3-4):72-101, 1904.Google Scholar
Daniel A., Spielman and Shang Hua, Teng. Spectral partitioning works: planar graphs and finite element meshes. In IEEE Symposium on Foundations of Computer Science, pages 96–105, 1996.
Robert F., Sproull. Refinements to nearest-neighbor searching in k-dimensional trees. Algorithmica, 6(4):579–589, 1991.Google Scholar
H., Sridharan, H., Sundaram, and T., Rikakis. Computational models for experiences in the arts, and multimedia. In ETP '03: Proceedings of the 2003 ACM SIGMM Workshop on Experiential Telepresence, pages 31–44, 2003.
K., Sripanidkulchai. The popularity of Gnutella queries and its implications on scalability. (Online http://www.cs.cmu.edu/ikunwadee/research/p2p/gnutella.html, February 2001).
H., Steinhaus. Sur la division des corp materiels en parties. Bull. Acad. Polon. Sci., C1. III, IV:801-804, 1956.Google Scholar
M.A., Stephens. EDF statistics for goodness of fit and some comparisons. J. Am. Statist. Assoc., 69(347):730–737, 1974.Google Scholar
S. S., Stevens, J., Volkmann, and E. B., Newman. A scale for the measurement of the psychological magnitude pitch. J. Acoust. Soc. Am., 8(3):185–190, 1937.Google Scholar
William J., Stewart and Wei, Wu. Numerical experiments with iteration and aggregation for Markov chains. ORSA J. Comput., 4:336–350, 1992.Google Scholar
G. C., Stockman and A. K., Agrawala. Equivalence of Hough curve detection to template matching. Commun. ACM, 20(11):820–822, 1977.Google Scholar
Michael, Stonebraker, Lawrence A., Rowe, Bruce G., Lindsay, Jim, Gray, Michael J., Carey, Michael L., Brodie, Philip A., Bernstein, and David, Beech. Third-generation database system manifesto. SIGMOD Rec., 19(3):31–44, 1990.Google Scholar
Michael, Stonebraker, Daniel J., Abadi, Adam, Batkin, Xuedong, Chen, Mitch, Cherniack, Miguel, Ferreira, Edmond, Lau, Amerson, Lin, Samuel R., Madden, Elizabeth J., O'Neil, Patrick E., O'Neil, Alexander Rasin, Nga Tran, and Stan B. Zdonik. C-store: a column-oriented DBMS. In VLDB, pages 553–564, Trondheim, Norway, 2005.
Jimeng, Sun, Dacheng, Tao, and Christos, Faloutsos. Beyond streams and graphs: dynamic tensor analysis. In KDD '06: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 374–383, 2006.
Daniel M., Sunday. A very fast substring search algorithm. Commun. ACM, 33(8), 1990.Google Scholar
Erkki, Sutinen and Jorma, Tarhio. On using q-gram locations in approximate string matching. In ESA '95: Proceedings of the Third Annual European Symposium on Algorithms, pages 327-340. Springer-Verlag, 1995.
K.-C., Tai. The tree-to-tree correction problem. J. ACM, 26:422–433, 1979.Google Scholar
Tadao, Takaoka. Approximate pattern matching with samples. In ISAAC, pages 234-242, 1994.
Kian-Lee, Tan, Pin-Kwang, Eng, and Beng Chin, Ooi. Efficient progressive skyline computation. In VLDB, pages 301–310, 2001.
Pang-Ning, Tan, Vipin, Kumar, and Jaideep, Srivastava. Selecting the right objective measure for association analysis. Inform. Syst., 29(4):293–313, 2004.Google Scholar
Yufei, Tao, Christos Faloutsos, and Dimitris Papadias. The power-method: a comprehensive estimation technique for multi-dimensional queries. In CIKM, pages 83-90, 2003.
Yufei, Tao, Ke, Yi, Cheng, Sheng, and Panos, Kalnis. Quality and efficiency in high dimensional nearest neighbor search. In SIGMOD '09: Proceedings of the 35th SIGMOD International Conference on Management ofData, pages 563–576, 2009.
Yee Whye, Teh, Michael I., Jordan, Matthew J., Beal, and David M., Blei. Hierarchical dirichlet processes. J. Am. Statist. Assoc., 101, 2003.Google Scholar
Kengo, Terasawa and Yuzuru, Tanaka. Spherical LSH for approximate nearest neighbor search on unit hypersphere. In Workshop on Algorithms and Data Structures (WADS), Volume 4619 of Lecture Notes in Computer Science, pages 27–38, 2007.
Martin, Theobald, Gerhard, Weikum, and Ralf, Schenkel. Top-k query evaluation with probabilistic guarantees. In VLDB, pages 648–659, 2004.
Yannis, Theodoridis, Emmanuel, Stefanakis, and Timos, Sellis. Efficient cost models for spatial queries using R-trees. IEEE Trans. Knowl. Data Eng., 12(1):19–32, 2000.Google Scholar
R., Tibshirani. Regression shrinkage and selection via the lasso. J. R. Statist. Soc. (Ser. B), 58:267–288, 1996.Google Scholar
David A., Tolliver and Gary L., Miller. Graph partitioning by spectral rounding: Applications in image segmentation and clustering. In CVPR '06: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 1053–1060, 2006.
W. S., Torgerson. Multidimensional scaling: I. Theory and method. Psychometrika, 17:401–419, 1952.Google Scholar
Caetano, Traina Jr., Agma Traina, Agma Jr., Traina, Leejay, and Wu Christos, Faloutsos. Fast feature selection using fractal dimension. In XV Brazilian Symposium on Databases (SBBD, pages 158–171, 2000.
Panayiotis, Tsaparas, Themistoklis, Palpanas, Yannis, Kotidis, Nick, Koudas, and Di-vesh, Srivastava. Ranked join indices. In ICDE, pages 277–288, 2003.
Charalampos E., Tsourakakis. Fast counting of triangles in large real networks without counting: algorithms and laws. In ICDM '08: Proceedings of the Eighth IEEE International Conference on Data Mining, pages 608–617, 2008.
Maurizio, Tucci, Gennaro, Costagliola, and Shi-Kuo, Chang. A remark on NP-completeness of picture matching. Inf. Process. Lett., 39(5):241–243, 1991.Google Scholar
Ledyard R., Tucker. Some mathematical notes on three-mode factor analysis. Psy-chometrika, (31):279-311, 1966.Google Scholar
J. K., Uhlmann. Metric trees. Appl. Math. Lett., 4(5):61–62, 1991.Google Scholar
E., Ukkonen. Finding approximate patterns in strings. J. Algorithms, 6:132–137, 1985.Google Scholar
E., Ukkonen. Approximate string-matching with q-grams and maximal matches. Theoret. Comp. Sci. 92, pages 191–211, 1992a.
Esko, Ukkonen. Constructing suffix trees on-line in linear time. In Proceedings of the IFIP 12th World Computer Congress on Algorithms, Software, Architecture -Information Processing '92, Volume 1, pages 484-492. North-Holland, 1992b.
J. R., Ullmann. An algorithm for subgraph isomorphism. J. ACM, 23(1):31–42, 1976.Google Scholar
Julian R., Ullmann. A binary n-gram technique for automatic correction of substitution, deletion, insertion and reversal errors in words. Comput. J., 20(2):141–147, 1977.Google Scholar
Tanguy, Urvoy, Emmanuel Chauveau, Pascal Filoche, and Thomas Lavergne. Tracking web spam with HTML style similarities. ACM Trans. Web, 2(1):1–28, 2008.Google Scholar
Jouko, Vaananen. Second-order logic and foundations of mathematics. Bull. Symbolic Logic, 7(4):504–520, 2001.Google Scholar
Gabriel, Valiente. An efficient bottom-up distance between trees. In Eighth International Symposium on String Processing and Information Retrieval (SPIRE'01), pages 212–219, 2001.
Peter, van Beek. Approximation algorithms for temporal reasoning. In Proceedings of the 11th International Joint Conference on Artificial Intelligence, pages 1291–1296, 1989.
C. J., van Rijsbergen, D. J., Harper, and M. F., Porter. The selection of good search terms. Inform. Process. Management, 17:77–91, 1981.Google Scholar
C. J., van Rijsbergen. Information Retrieval, 2nd ed. Butterworths, London, 1979.
V., Vapnik. Estimation of Dependencies Based on Empirical Data. Nauka, Moscow, 1979.
M., Vazirgiannis and S., Boll. Events in interactive multimedia applications: modeling and implementation design. In ICMCS '97: Proceedings of the 1997 International Conference on Multimedia Computing and Systems (ICMCS '97), page 244. IEEE Computer Society, 1997.
Sriharsha, Veeramachaneni, Diego, Sona, and Paolo, Avesani. Hierarchical dirichlet model for document classification. In ICML '05: Proceedings of the 22nd International Conference on Machine Learning, pages 928–935, 2005.
Enrique, Vidal. New formulation and improvements of the nearest-neighbour approximating and eliminating search algorithm (aesa). Pattern Recogn. Lett., 15 (1):1-7, 1994.Google Scholar
Karane, Vieira, André Luiz Costa, Carvalho, Klessius, Berlt, Edleno S., Moura, Altigran S., Silva, and Juliana, Freire. On finding templates on web collections. World Wide Web, 12(2):171–211, 2009.Google Scholar
M., Vilain and H., Kautz. Constraint propagation algorithms for temporal reasoning. In Proceedings of AAAI- 86, Artificial Intelligence, pages 377–382, 1986.
Juan Miguel, Vilar. Reducing the overhead of the aesa metric-space nearest neighbour searching algorithm. Inform. Process. Lett., 56(5):265–271, 1995.Google Scholar
Luc, Vincent and Pierre, Soille. Watersheds in digital spaces: an efficient algorithm based on immersion simulations. IEEE Trans. Pattern Anal. Mach. Intell., 13(6): 583-598, 1991.Google Scholar
S., Vishwanathan and A., Smola. Fast kernels for string and tree matching. In K., Tsuda, B., Scholkopf, and J. P., Vert, editors, Kernels and Bioinformatics. MIT Press, 2003.
A. J., Viterbi. Error bounds for convolution codes and an asymptotically optimum decoding algorithm. IEEE. Trans. Inform. Theory, 13(2):260–269, 1967.Google Scholar
Willem, Waegeman and Luc, Boullart. An ensemble of weighted support vector machines for ordinal regression. In Proceedings of World Academy of Science, Engineering and Technology, Volume 12, March 2006.
Jason Tsong-Li, Wang and Kaizhong, Zhang. Finding similar consensus between trees: an algorithm and a distance hierarchy. Pattern Recogn., 34(1):127–137, 2001.Google Scholar
Tsong-Li, Wang and Dennis, Shasha. Query processing for distance metrics. In Proceedings of the Sixteenth International Conference on Very Large Databases, pages 602–613, 1990.
Xuanhui, Wang, Hui, Fang, and Cheng Xiang, Zhai. Improve retrieval accuracy for difficult queries using negative feedback. In CIKM '07: Proceedings of the Sixteenth ACM Conference on Information and Knowledge Management, pages 991-994, 2007.
Xuanhui, Wang, Hui, Fang, and Cheng Xiang, Zhai. A study of methods for negative relevance feedback. In SIGIR '08: Proceedings of the 31st annual international ACM SIGIR Conference on Research and Development in Information Retrieval, pages 219–226, 2008.
Ying-Hong, Wang. Image indexing and similarity retrieval based on a new spatial relation model. In International Conference on Distributed Computing Systems, Workshop, pages 396–401, 2001.
Stanley, Wasserman, Katherine, Faust, and Dawn, Iacobucci. Social Network Analysis: Methods and Applications (Structural Analysis in the Social Sciences). Cambridge University Press, November 1994.
D. J., Watts and S. H., Strogatz. Collective dynamics of “small-world” networks. Nature, 393(6684):440–442, June 1998.Google Scholar
David L., Weakliem. A critique of the Bayesian information criterion for model selection. Sociol. Methods Res., 27:359–397, 1999.Google Scholar
Roger, Weber and Stephen, Blott. A quantitative analysis and performance study for similarity-search methods in high-dimensional spaces. In Proceedings of the 24th International Conference on Very Large Data Bases (VLDB), pages 194–205, 1998.
Ron, Weiss, Andrzej, Duda, and David K., Gifford. Content-based access to algebraic video. In International Conference on Multimedia Computing and Systems, IEEE, pages 140–151, 1994.
L. R., Welch. Hidden Markov models and the Baum-Welch algorithm. IEEE Inform. Theory Soc. Newsl., 53(4), December 2003.Google Scholar
Utz, Westermann and Ramesh, Jain. Toward a common event model for multimedia applications. IEEE MultiMedia, 14(1):19–29, 2007.Google Scholar
David A., White and Ramesh, Jain. Similarity indexing with the SS-tree. In ICDE '96: Proceedings of the Twelfth International Conference on Data Engineering, pages 516-523, 1996a.
David A., White and Ramesh, Jain. Similarity indexing: Algorithms and performance. In Storage and Retrieval for Image and Video Databases (SPIE), 1996b.
Frank, Wilcoxon. Individual comparisons by ranking methods. Biometrics Bull., 1(6):80–83, 1945.Google Scholar
Christopher K. I., Williams and Matthias, Seeger. Using the Nystrom method to speed up kernel machines. In T., Leen, T., Dietterich, and V., Tresp, editors, Neural Information Processing Systems 13, pages 682-688. MIT Press, 2001.
Stefan, Wirag. Scheduling of adaptive multimedia documents. In ICMCS '99: Proceedings of the IEEE International Conference on Multimedia Computing and Systems, Volume 2, page 307. IEEE Computer Society, 1999.
Dian I., Witter and Michael W., Berry. Downdating the latent semantic indexing model for conceptual information retrieval. Comput. J., 41(8):589–601, 1998.Google Scholar
Raymond Chi-Wing, Wong, Ada Wai-Chee, Fu, Jian, Pei, Yip Sing, Ho, Tai, Wong, and Yubao, Liu. Efficient skyline querying with variable user preferences on nominal attributes. Proc. VLDB, 1(1):1032–1043, 2008.Google Scholar
M. F., Worboys, H. M., Hearnshaw, and D. J., Maguire. Object-oriented data modelling for spatial databases. Int. J. Geograph. Inform. Syst., 4:369–383, 1990.Google Scholar
G. H., Wu, Y.J., Zhang, and X.G., Lin. Wavelet transform-based texture classification with feature weighting. In ICIP99, pages IV:435-439, 1999.
Sun, Wu and Udi, Manber. Fast text searching with errors. tr 9111. Technical report, Department of Computer Science, University of Arizona., 1991.
Sun, Wu and Udi, Manber. Fast text searching: allowing errors. Commun. ACM, 35 (10):83-91, 1992.Google Scholar
Zhibiao, Wu and Martha, Palmer. Verbs semantics and lexical selection. In Proceedings of the 32nd Annual Meeting of the Association for Computational Linguistics, pages 133–138, 1994.
Dong, Xin, Chen, Chen, and Jiawei, Han. Towards robust indexing for ranked queries. In VLDB '06: Proceedings of the 32nd International Conference on Very Large Data Bases, pages 235–246, 2006.
Dong, Xin, Jiawei, Han, and Kevin C., Chang. Progressive and selective merge: computing top-k with ad-hoc ranking functions. In SIGMOD '07: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pages 103-114, 2007.
R. R., Yager. Some procedures for selecting fuzzy set-theoretic operations. Int. J. General Syst., 8:115–124, 1982.Google Scholar
P., Yamuna, N., Cho, K. Selçuk, Candan, and M., Wagner. Towards an open repository for VRML. In International Symposium on Computer and Information Sciences, 1999.
Prakash, Yamuna and K. Selçuk, Candan. Efficient similarity-based retrieval of temporal structures. In SAINT-W '01: Proceedings of the 2001 Symposium on Applications and the Internet-Workshops (SAINT2001 Workshops), pages 133–138, Jan 2001.
Wuu, Yang. Identifying syntactic differences between two programs. Softw. Pract. Exper., 21(7):739–755, 1991.Google Scholar
Mihalis, Yannakakis. Graph-theoretic methods in database theory. In PODS '90: Proceedings of the Ninth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, pages 230–242, 1990.
Peter N., Yianilos. Data structures and algorithms for nearest neighbor search in general metric spaces. In SODA '93: Proceedings of the Fourth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 311–321, 1993.
Hujun, Yin. Data visualisation and manifold mapping using the visom. Neural Netw., 15(8-9):1005-1016, 2002.Google Scholar
Hujun, Yin. Learning Nonlinear Principal Manifolds by Self-Organising Maps, in Principal Manifolds for Data Visualization and Dimension Reduction, Springer, pages 68–95, 2007.
Xiaoxin, Yin, Jiawei, Han, and Philip S., Yu. Linkclus: efficient clustering via heterogeneous semantic links. In VLDB '06: Proceedings of the 32nd International Conference on Very Large Data Bases, pages 427–438, 2006.
Xiaoxin, Yin, Jiawei, Han, and Philip S., Yu. Object distinction: Distinguishing objects with identical names. In ICDE, pages 1242–1246, 2007.
Man Lung, Yiu and Nikos, Mamoulis. Efficient processing of top-k dominating queries on multi-dimensional data. In VLDB '07: Proceedings of the 33rd International Conference on Very Large Data Bases, pages 483–494, 2007.
C. T., Yu, W. S., Luk, and T. Y., Cheung. A statistical model for relevance feedback in information retrieval. J. ACM, 23(2):273–286, 1976.Google Scholar
Clement, Yu, Prasoon, Sharma, Weiyi, Meng, and Yan, Qin. Database selection for processing k nearest neighbors queries in distributed environments. In JCDL '01: Proceedings of the 1st ACM/IEEE-CS Joint Conference on Digital Libraries, pages 215–222, 2001.
Clement, Yu, George, Philip, and Weiyi, Meng. Distributed top-n query processing with possibly uncooperative local systems. In VLDB 2003, Proceedings of 29th International Conference on Very Large Data Bases, September 9-12, 2003, pages 117-128. Morgan Kaufmann, 2003.
Clement T., Yu and Weiyi, Meng. Principles of Database Query processing for Advanced Applications. Morgan Kaufmann, San Francisco, CA, USA, 1998.
Jie, Yu, Jaume, Amores, Nicu, Sebe, Petia, Radeva, and Qi, Tian. Distance learning for similarity estimation. IEEE Trans. Pattern Anal. Mach. Intell., 30(3):451–462, 2008.Google Scholar
L. A., Zadeh. Fuzzy sets. Inform. Control, 8:338–353, 1965.Google Scholar
L. A., Zadeh. The concept of a linguistic variable and its application to approximate reasoning-i. Inform. Sci., 8:199–249, 1975.Google Scholar
Hongyuan, Zha and Horst D., Simon. On updating problems in latent semantic indexing. SIAMJ. Sci. Comput., 21(2):782–791, 1999.Google Scholar
Chengxiang, Zhai and John, Lafferty. Model-based feedback in the language modeling approach to information retrieval. In CIKM '01: Proceedings of the Tenth International Conference on Information and Knowledge Management, pages 403–410, 2001.
Chengxiang, Zhai and John, Lafferty. A study of smoothing methods for language models applied to information retrieval. ACM Trans. Inform. Syst., 22(2):179–214, 2004.Google Scholar
Chi, Zhang and P., Wang. A new method of color image segmentation based on intensity and hue clustering. ICPR, volume 3, page 613-616, 2000.Google Scholar
K., Zhang and D., Shasha. Simple fast algorithms for the editing distance between trees and related problems. SIAMJ. Comput., 18(6):1245–1262, 1989.Google Scholar
K., Zhang, J. T. L., Wang, and D., Shasha. On the editing distance between undirected acyclic graphs. Int. J. Comp. Sci., 7(1):43–57, 1996.Google Scholar
Kaizhong, Zhang, Rick, Statman, and Dennis, Shasha. On the editing distance between unordered labeled trees. Inform. Process. Lett., 42(3):133–139, 1992.Google Scholar
Q.-L., Zhang. A remark on intractability of picture retrieval by contents. Technical Report, University of Illinois, 1994.
Q.-L., Zhang and S. S.-T., Yau. On intractability of spatial relationships in content-based image database systems. Commun. Inform. Syst., 4(2):181–190, 2005.Google Scholar
Zhen, Zhang, Seung-won, Hwang, Kevin Chen-Chuan, Chang, Min, Wang, Christian A., Lang, and Yuan-chi, Chang. Boolean + ranking: querying a database by k-constrained optimization. In SIGMOD '06: Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data, pages 359–370, 2006.
Yi, Zhou and T., Murata. Fuzzy-timing Petri net model for distributed multimedia synchronization. In 1998 IEEE International Conference on Systems, Man, and Cybernetics, Volume 1, pages 244-249, 1998.
George K., Zipf. Human Behavior and the Principle of Least Effort. Addison-Wesley, Reading, MA, 1949.
Jacob, Ziv and Abraham, Lempel. A universal algorithm for sequential data compression. IEEE Trans. Inform. Theory, 23:337–343, 1977.Google Scholar
Jacob, Ziv and Neri, Merhav. A measure of relative entropy between individual sequences with application to universal classification. IEEE Trans. Inform. Theory, 39(4):1270–1279, 1993.Google Scholar
J., Zobel and A., Moffat. Inverted files for text search engines. Computing Surveys, 38:1–56, 2006.Google Scholar
Justin, Zobel, Alistair, Moffat, and Kotagiri, Ramamohanarao. Inverted files versus signature files for text indexing. ACM Trans. Database Syst., 23(4):453–490, 1998.Google Scholar
A., Zunjarwad, H., Sundaram, and L., Xie. Contextual wisdom: social relations and correlations for multimedia event annotation. In Proceedings ofACM Multimedia, pages 615–624, 2007.

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  • Book: Data Management for Multimedia Retrieval
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