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Data Management for Multimedia Retrieval

$108.00 (P)

  • Date Published: May 2010
  • availability: In stock
  • format: Hardback
  • isbn: 9780521887397

$ 108.00 (P)
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  • Multimedia data require specialized management techniques because the representations of color, time, semantic concepts, and other underlying information can be drastically different from one another. The user’s subjective judgment can also have significant impact on what data or features are relevant in a given context. These factors affect both the performance of the retrieval algorithms and their effectiveness. This textbook on multimedia data management techniques offers a unified perspective on retrieval efficiency and effectiveness. It provides a comprehensive treatment, from basic to advanced concepts, that will be useful to readers of different levels, from advanced undergraduate and graduate students to researchers and to professionals. After introducing models for multimedia data (images, video, audio, text, and web) and for their features, such as color, texture, shape, and time, the book presents data structures and algorithms that help store, index, cluster, classify, and access common data representations. The authors also introduce techniques, such as relevance feedback and collaborative filtering, for bridging the “semantic gap” and present the applications of these to emerging topics, including web and social networking.

    • Focuses in a balanced manner on both 'data structures/databases' and 'mining/retrieval' aspects of multimedia data management. Most other books in the area cover only one or the other
    • Organized in terms of basic data models (vectors, strings, trees, graphs, and fuzzy/probabilistic representations) that cover a large spectrum of media types instead of being limited to one or two special media types (such as images)
    • Each topic is covered from basic to advanced concepts; thus the book can be of interest to readers of different levels
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    Reviews & endorsements

    "This text book is a complete and excellent treatment of multimedia information retrieval and data management. It handles the entire spectrum by providing the basic theory needed and then gradually introduces the advanced techniques needed to tackle the complex issues in multimedia content retrieval."
    B. Prabhakaran, University of Texas at Dallas

    "An excellent and comprehensive resource on multimedia data management systems, ranging from basic multimedia data- and storage models to indexing, query and retrieval techniques specifically adapted to the intricacies of multimedia. This textbook is suited both for students to gain theoretical insight in the full range of components required for such a system, or developers who want to build or improve systems."
    Marcel Worring, Intelligent Systems Lab Amsterdam, University of Amsterdam

    This is a very timely book which fills a long felt gap of a comprehensive textbook possessing depth in the Multimedia Information Systems area. With a distinctively database systems perspective, it provides a refreshingly detailed and balanced treatment of the necessary multimedia content processing fundamentals. This book can serve as the reference text for senior undergraduate and graduate courses in Multimedia Information Systems. It will also be an excellent self-contained take-off point for beginning researchers in Multimedia Information Retrieval and Multimedia Databases. Moreover, Multimedia Signal Processing researchers can use it to gain a solid understanding of the Database Systems issues."
    Mohan S.  Kankanhalli, School of Computing, National University of Singapore

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    Product details

    • Date Published: May 2010
    • format: Hardback
    • isbn: 9780521887397
    • length: 500 pages
    • dimensions: 260 x 185 x 28 mm
    • weight: 1.04kg
    • contains: 195 b/w illus. 15 tables
    • availability: In stock
  • Table of Contents

    1. Introduction: multimedia applications and data management requirements
    2. Models for multimedia data
    3. Common representations of multimedia features
    4. Feature quality and independence: why and how?
    5. Indexing, search, and retrieval of sequences
    6. Indexing, search, retrieval of graphs and trees
    7. Indexing, search, and retrieval of vectors
    8. Clustering techniques
    9. Classification
    10. Ranked retrieval
    11. Evaluation of retrieval
    12. User relevance feedback and collaborative filtering.

  • Authors

    K. Selçuk Candan, Arizona State University
    K. Selçuk Candan is a Professor of Computer Science and Engineering at Arizona State University. He received his Ph.D. in 1997 from the University of Maryland at College Park. Candan has authored more than 120 conference and journal articles, 9 patents, and many book chapters and, among his other scientific positions, has served as program chair for ACM Multimedia Conference '08, the Int. Conference on Image and Video Retrieval (CIVR'10), and as an organizing committee member for ACM SIG Management of Data Conference (SIGMOD'06). Since 2005, he has also served as an editorial board member for the Very Large Databases (VLDB) journal.

    Maria Luisa Sapino, Università degli Studi di Torino, Italy
    Maria Luisa Sapino is a Professor in the Department of Computer Science at the University of Torino, where she also earned her Ph.D. There she leads the multimedia and heterogeneous data management group. Her scientific contributions include more than 60 conference and journal papers; her services as chair, organizer, and program committee member in major conferences and workshops on multimedia; and her collaborations with industrial research labs, including the RAI-Crit (Center for Research and Technological Innovation) and Telecom Italia Lab, on multimedia technologies.

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