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Web-STAR: A Visual Web-based IDE for a Story Comprehension System

Published online by Cambridge University Press:  14 November 2018

CHRISTOS T. RODOSTHENOUS
Affiliation:
Open University of Cyprus, Nicosia, Cyprus (e-mail: christos.rodosthenous@ouc.ac.cy)
LOIZOS MICHAEL
Affiliation:
Open University of Cyprus and Research Center on Interactive Media, Smart Systems, and Emerging Technologies, Nicosia, Cyprus (e-mail: loizos@ouc.ac.cy)

Abstract

We present Web-STAR, an online platform for story understanding built on top of the STAR reasoning engine for STory comprehension through ARgumentation. The platform includes a web-based integrated development environment, integration with the STAR system, and a web service infrastructure to support integration with other systems that rely on story understanding functionality to complete their tasks. The platform also delivers a number of “social” features, including a community repository for public story sharing with a built-in commenting system, and tools for collaborative story editing that can be used for team development projects and for educational purposes.

Type
Original Article
Copyright
Copyright © Cambridge University Press 2018 

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Footnotes

The authors would like to thank: Adamos Koumis, for his collaboration in the development of the component that converts natural language to the STAR syntax; Elektra Kypridemou, for her help in the preparation of the evaluation methodology; and the anonymous reviewers, for their valuable comments and suggestions.

An earlier version of this work was presented at the 2nd International Workshop on User-Oriented Logic Paradigms (IULP 2017). This article presents a newer version of the Web-STAR IDE with additional implemented features, along with the results of a user evaluation conducted to verify the usability and learnability of the IDE.

References

Abbott, H. P. 2008. The Cambridge Introduction to Narrative. Cambridge University Press.CrossRefGoogle Scholar
Balai, E., Gelfond, M. and Zhang, Y. 2013. Towards Answer Set Programming with Sorts. Springer, Berlin, Heidelberg, 135147.Google Scholar
Bangor, A., Kortum, P. and Miller, J. 2009. Determining what individual SUS scores mean: Adding an adjective rating scale. Journal of Usability Studies 4, 3, 114123.Google Scholar
Barnum, C. M. 2001. Usability Testing and Research, 1st ed. Allyn & Bacon, Inc., Needham Heights, MA, USA.Google Scholar
Baroni, P., Caminada, M. and Giacomin, M. 2011. An introduction to argumentation semantics. The Knowledge Engineering Review 26, 4, 365410.CrossRefGoogle Scholar
Bench-Capon, T. and Dunne, P. E. 2007. Argumentation in artificial intelligence. Artificial Intelligence 171, 10–15, 619641.CrossRefGoogle Scholar
Besnard, P. and Hunter, A. 2008. Elements of Argumentation, vol. 47. MIT Press, Cambridge, MA, USA.CrossRefGoogle Scholar
Blackmon, M. H., Polson, P. G., Kitajima, M. and Lewis, C. 2002. Cognitive walkthrough for the web. In Proc. of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’02. Minneapolis, Minnesota, USA, 20–25 Apr. 2002, ACM, New York, NY, USA, 463470.Google Scholar
Bogaard, T., Wielemaker, J., Hollink, L. and Van Ossenbruggen, J. 2017. SWISH DataLab: A Web Interface for Data Exploration and Analysis. Springer International Publishing, Cham, Switzerland, 181187.Google Scholar
Brandes, U., Eiglsperger, M., Lerner, J. and Pich, C. 2013. Graph Markup Language (GraphML). In Handbook of Graph Drawing Visualization, Tamassia, R., Ed. Discrete mathematics and its applications. CRC Press, Boca Raton, FL [u.a.], 517541.Google Scholar
Brooke, J. 1996. SUS– A quick and dirty usability scale. Usability Evaluation in Industry 189, 194, 47.Google Scholar
Buhrmester, M., Kwang, T. and Gosling, S. D. 2011. Amazon’s Mechanical Turk. Perspectives on Psychological Science 6, 1, 35.CrossRefGoogle Scholar
Carroll, N. 2001. On the narrative connection. In Beyond Aesthetics: Philosophical Essays, Cambridge University Press, 118133.CrossRefGoogle Scholar
Charniak, E. 1972. Toward a Model of Children’s Story Comprehension. Tech. Rep. AITR-266, Cambridge, MA, USA.Google Scholar
Charniak, E. 1977. Ms. Maloprop, a language comprehension program. In Proc. of the 5th International Joint Conference on Artificial Intelligence, vol. 1. IJCAI’77, Cambridge, Massachusetts, USA, 22–25 Aug. 1977, Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 17.Google Scholar
Cloud9 IDE. 2017. Cloud9 IDE. URL: http://c9.io/. [Accessed on April 18, 2017].Google Scholar
Codeanywhere Inc. 2017. Codeanywhere IDE. URL: https://codeanywhere.com/. [Accessed on April 18, 2017].Google Scholar
Corcoglioniti, F., Rospocher, M. and Palmero Aprosio, A. 2016. Frame-based ontology population with PIKES. IEEE Transactions on Knowledge and Data Engineering 28, 12, 32613275.CrossRefGoogle Scholar
Dasseville, I. and Janssens, G. 2015. A web-based IDE for IDP. In 1st International Workshop on User-Oriented Logic Programming (IULP2015).Google Scholar
Davis, E. 1990. Representations of Commonsense Knowledge. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA.Google Scholar
Denecker, M. and Ternovska, E. 2008. A logic of nonmonotone inductive definitions. ACM Transactions on Computational Logic 9, 2 (Apr.), 14:114:52.Google Scholar
Diakidoy, I.-A., Kakas, A., Michael, L. and Miller, R. 2014. Story comprehension through argumentation. In Proc. of the 5th International Conference on Computational Models of Argument (COMMA 2014), Scottish Highlands, UK, 9–12 Sep. 2014, Parsons, S., Oren, N., Reed, C., and Cerutti, F., Eds. IOS Press, 3142.Google Scholar
Diakidoy, I.-A., Kakas, A., Michael, L. and Miller, R. 2015. STAR: A system of argumentation for story comprehension and beyond. In Working Notes of the 12th International Symposium on Logical Formalizations of Commonsense Reasoning (Commonsense 2015), 6470.Google Scholar
Eason, K. D. 2005. Information Technology and Organisational Change. Taylor & Francis.Google Scholar
Eclipse Foundation. 2017. Eclipse Che IDE. URL: https://eclipse.org/che/. [Accessed on April 18, 2017].Google Scholar
Forster, E. M. 2010. Aspects of the Novel. RosettaBooks.Google Scholar
Franz, M., Lopes, C. T., Huck, G., Dong, Y., Sumer, O. and Bader, G. D. 2016. Cytoscape.js: A graph theory library for visualisation and analysis. Bioinformatics 32, 2, 309311.Google Scholar
Friedman, M. 1974. Explanation and scientific understanding. The Journal of Philosophy 71, 1, 519.CrossRefGoogle Scholar
Genette, G. 1982. Figures of Literary Discourse. European perspectives: A series in social thought and cultural criticism. Columbia University Press.Google Scholar
Goldman, S. R., Graesser, A. C. and Broek, P. V. D. 1999. Narrative Comprehension, Causality, and Coherence: Essays in Honor of Tom Trabasso. Taylor & Francis.Google Scholar
Hirschman, L., Light, M., Breck, E. and Burger, J. D. 1999. Deep read: A reading comprehension system. In Proc. of the 37th Annual Meeting of the Association for Computational Linguistics on Computational Linguistics, College Park, Maryland, USA, 20–26 Jun. 1999. Association for Computational Linguistics, Stroudsburg, PA, USA, 325332.CrossRefGoogle Scholar
ICEcoder Ltd. 2017. ICEcoder IDE. URL: https://icecoder.net/. [Accessed on April 18, 2017].Google Scholar
Iyyer, M., Manjunatha, V., Guha, A., Vyas, Y., Boyd-Graber, J. L., Daume, H. III and Davis, L. S. 2016. The amazing mysteries of the gutter: Drawing inferences between panels in comic book narratives. CoRR abs/1611.0.Google Scholar
John, B. E. and Packer, H. 1995. Learning and using the cognitive walkthrough method: A case study approach. In Proc. of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’95. Denver, Colorado, USA, 07–11 May, Katz, I. R., Mack, R., Marks, L., Rosson, M. B., and Nielsen, J., Eds. ACM Press/Addison-Wesley Publishing Co., New York, NY, USA, 429436.CrossRefGoogle Scholar
Johnston, A. B. and Burnett, D. C. 2012. WebRTC: APIs and RTCWEB Protocols of the HTML5 Real-Time Web. Digital Codex LLC, USA.Google Scholar
Kakas, A. and Michael, L. 2016. Cognitive systems: Argument and cognition. IEEE Intelligent Informatics Bulletin 17, 1, 1420.Google Scholar
Katz, B. 1997. Annotating the World Wide Web using natural language. In Computer-Assisted Information Searching on Internet. RIAO ’97. LE CENTRE DE HAUTES ETUDES INTERNATIONALES D’INFORMATIQUE DOCUMENTAIRE, Paris, France, 136155.Google Scholar
Kline, R. B. and Seffah, A. 2005. Evaluation of integrated software development environments: Challenges and results from three empirical studies. International Journal of Human-Computer Studies 63, 6 (Dec.), 607627.CrossRefGoogle Scholar
Kowalski, R. and Sadri, F. 2016. Programming in logic without logic programming. Theory and Practice of Logic Programming 16, 3 (May), 269295.CrossRefGoogle Scholar
Lenat, D. 1995. CYC: A large-scale investment in knowledge infrastructure. Communications of the ACM 38, 11, 3338.CrossRefGoogle Scholar
Lenat, D. B. and Guha, R. V. 1990. Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project, 1st ed. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA.Google Scholar
Lewis, J. R., Utesch, B. S. and Maher, D. E. 2015. Measuring perceived usability: The SUS, UMUX-LITE, and AltUsability. International Journal of Human-Computer Interaction 31, 8, 496505.CrossRefGoogle Scholar
Macefield, R. 2009. How to specify the participant group size for usability studies: A practitioner’s guide. Journal of Usability Studies 5, 1, 3445.Google Scholar
Mahdisoltani, F., Biega, J. and Suchanek, F. M. 2015. YAGO3: A knowledge base from multilingual wikipedias. In Proc. of 7th Biennial Conference on Innovative Data Systems Research (CIDR), Asilomar, California, USA, 4–7 Jan. 2015, www.cidrdb.org [Online proceedings], 111.Google Scholar
Manning, C. D., Bauer, J., Finkel, J., Bethard, S. J., Surdeanu, M. and McClosky, D. 2014. The Stanford CoreNLP natural language processing toolkit. In Proc. of the 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations, Baltimore, Maryland, USA, 22–27 Jun. 2014, Association for Computational Linguistics (ACL), 5560.Google Scholar
Marcopoulos, E., Reotutar, C. and Zhang, Y. 2017. An online development environment for answer set programming. In 2nd International Workshop on User-Oriented Logic Paradigms (IULP 2017).Google Scholar
Michael, L. 2009. Reading between the lines. In Proc. of the 21st International Joint Conference on Artificial Intelligence (IJCAI 2009), Pasadena, California, USA, 11–17 Jul. 2009, IJCAI Organization, 15251530.Google Scholar
Michael, L. 2013. Story understanding... Calculemus. In Proc. of the 11th International Symposium on Logical Formalizations of Commonsense Reasoning (Commonsense’13), Ayia Napa, Cyprus, 27–29 May 2013, [online proceedings].Google Scholar
Michael, L. 2016. Cognitive reasoning and learning mechanisms. In 4th International Workshop on Artificial Intelligence and Cognition, vol. 1895, New York City, NY, USA, 6–16 Jul. 2016, Lieto, A., Bhatt, M., Oltramari, A., and Vernon, D., Eds. CEUR Workshop Proceedings (CEUR-WS.org), 2–23.Google Scholar
Michael, L. 2017. The Advice Taker 2.0. In Proc. of the 13th International Symposium on Commonsense Reasoning (Commonsense 2017), vol. 2052. London, UK, 6–8 Nov. 2017, Gordon, A. S., Miller, R., and Turán, G., Eds. CEUR Workshop Proceedings (CEUR-WS.org).Google Scholar
Mitchell, T., Cohen, W., Hruschka, E., Talukdar, P., Betteridge, J., Carlson, A., Mishra, B. D., Gardner, M., Kisiel, B., Krishnamurthy, J., Lao, N., Mazaitis, K., Mohamed, T., Nakashole, N., Platanios, E., Ritter, A., Samadi, M., Settles, B., Wang, R., Wijaya, D., Gupta, A., Chen, X., Saparov, A., Greaves, M. and Welling, J. 2015. Never-ending learning. In AAAI Conference on Artificial Intelligence, 23022310.Google Scholar
Modgil, S. and Prakken, H. 2014. The ASPIC+ framework for structured argumentation: A tutorial. Argument & Computation 5, 1, 3162.CrossRefGoogle Scholar
Morgan, M. S. 2017. Narrative ordering and explanation. Studies in History and Philosophy of Science Part A 62, 8697.CrossRefGoogle ScholarPubMed
Mueller, E. T. 2000. Prospects for in-depth story understanding by computer. Cognitive Systems Research 23, 307340.Google Scholar
Mueller, E. T. 2003. Story understanding through multi-representation model construction. In Proc. of the HLT-NAACL 2003 Workshop on Text Meaning, vol. 9. HLT-NAACL- TEXTMEANING. Edmonton, Canada, 31 May 2003, Association for Computational Linguistics, Stroudsburg, PA, USA, 46–53.Google Scholar
Mueller, E. T. 2006. Story understanding. In Encyclopedia of Cognitive Science, Nadel, Lynn, Ed. John Wiley & Sons, Ltd.Google Scholar
Mueller, E. T. 2007. Modelling space and time in narratives about restaurants. Literary and Linguistic Computing 22, 1, 6784.CrossRefGoogle Scholar
Mueller, E. T. 2015. Commonsense Reasoning: An Event Calculus Based Approach, 2nd ed. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA.CrossRefGoogle Scholar
Ng, H. T., Teo, L. H. and Kwan, J. L. P. 2000. A machine learning approach to answering questions for reading comprehension tests. In Proc. of the 2000 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora: Held in Conjunction with the 38th Annual Meeting of the Association for Computational Linguistics, vol. 13. EMNLP ’00. Hong Kong, 7–8 Oct. 2000, Association for Computational Linguistics, Stroudsburg, PA, USA, 124–132.Google Scholar
Pansanato, L., Rivolli, A. and Pereira, D. 2015. An evaluation with web developers of capturing user interaction with rich Internet applications for usability evaluation. International Journal of Computer Science and Application 4, 2, 5160.CrossRefGoogle Scholar
Prince, G. 2003. A Dictionary of Narratology. University of Nebraska Press.Google Scholar
Rahwan, I. and Simari, G. R. 2009. Argumentation in Artificial Intelligence, 1st ed. Springer Publishing Company, Incorporated.Google Scholar
Rick Altman. 2008. A Theory of Narrative. Columbia University Press.Google Scholar
Ricoeur, P. 1980. Narrative time. Critical Inquiry 7, 1, 169190.CrossRefGoogle Scholar
Riloff, E. and Thelen, M. 2000. A rule-based question answering system for reading comprehension tests. In Proc. of the 2000 ANLP/NAACL Workshop on Reading Comprehension Tests As Evaluation for Computer-based Language Understanding Systems, vol. 6. ANLP/NAACL-ReadingComp ’00. Seattle, Washington, USA, 4 May 2000, Association for Computational Linguistics Stroudsburg, PA, USA, 1319.Google Scholar
Rodosthenous, C. and Michael, L. 2016. A hybrid approach to commonsense knowledge acquisition. In Proc. of the 8th European Starting AI Researcher Symposium, The Hague, Holland, 29–30 Aug. 2016, Pearce, D., and Pinto, H. S., Eds. IOS Press, 111122.Google Scholar
Roth, P. A. 1989. How narratives explain. Social Research 56, 2, 449478.Google Scholar
Ryan, M.-L. 2007. Toward a definition of narrative. In The Cambridge Companion to Narrative, Herman, D., Ed. Cambridge University Press, 2235.CrossRefGoogle Scholar
Safranski, K. 2017. Codiad Web Based, Cloud IDE. URL: http://codiad.com/. [Accessed on April 18, 2017].Google Scholar
Speer, R. and Havasi, C. 2013. ConceptNet 5: A Large Semantic Network for Relational Knowledge. Springer, Berlin, Heidelberg, 161176.Google Scholar
Toni, F. 2014. A tutorial on assumption-based argumentation. Argument & Computation 5, 1, 89117.CrossRefGoogle Scholar
UzZaman, N., Llorens, H., Derczynski, L., Verhagen, M., Allen, J. and Pustejovsky, J. 2013. SemEval-2013 Task 1: TempEval-3: Evaluating time expressions, events, and temporal relations. In Second joint Conference on Lexical and Computational Semantics (* SEM) 2, SemEval, 19.Google Scholar
Velleman, J. D. 2003. Narrative explanation. The Philosophical Review 112, 1, 125.Google Scholar
von Ahn, L. and Dabbish, L. 2008. Designing games with a purpose. Communications of the ACM 51, 8, 57.CrossRefGoogle Scholar
Wellner, B., Ferro, L., Grieff, W. and Hirschman, L. 2006. Reading comprehension tests for computer-based understanding evaluation. Natural Language Engineering 12, 4 (Dec.), 305334.CrossRefGoogle Scholar
Wharton, C., Rieman, J., Lewis, C. and Polson, P. 1994. The Cognitive Walkthrough Method: A Practitioner’s Guide. Tech. rep., New York, NY, USA.Google Scholar
Wielemaker, J., Lager, T. and Riguzzi, F. 2015. SWISH: SWI-Prolog for sharing. In 1st International Workshop on User-Oriented Logic Programming (IULP2015).Google Scholar
Wielemaker, J., Schrijvers, T., Triska, M. and Lager, T. 2012. SWI-Prolog. Theory and Practice of Logic Programming 12, 1–2, 6796.CrossRefGoogle Scholar
Winston, P. H. 2015. Model-based story summary. In 6th Workshop on Computational Models of Narrative (CMN 2015), Finlayson, M. A., Miller, B., Lieto, A., and Ronfard, R., Eds. OpenAccess Series in Informatics (OASIcs), vol. 45. Schloss Dagstuhl–Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany, 157–165.Google Scholar
Zhang, X., Zhao, J. and LeCun, Y. 2015. Character-level convolutional networks for text classification. In Advances in Neural Information Processing Systems 28, Cortes, C., Lawrence, N. D., Lee, D. D., Sugiyama, M., and Garnett, R., Eds. Curran Associates Inc., 649657.Google Scholar
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