Abstract
Creating a document model for efficient keyword search is a long studied problem in Information Retrieval. In this paper we explore the application of Tolerance Rough Set Model for Documents (TRSM) for this problem. We further provide an extension of TRSM with a weight learning procedure (TRSM-WL) and compare performance of these two algorithms in keyword search. We further provide a generalization of TRSM-WL that imposes additional constraints on the underlying model structure and compare it to a supervised variant of Explicit Semantic Analysis.
The authors are supported by grant 2012/05/B/ST6/03215 from the Polish National Science Centre (NCN), and the grant SP/I/1/77065/10 in frame of the strategic scientific research and experimental development program: “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information” founded by the Polish National Centre for Research and Development (NCBiR).
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References
Blair, D.C., Maron, M.E.: An evaluation of retrieval effectiveness for a full-text document-retrieval system. Commun. ACM 28(3), 289–299 (1985)
Furnas, G.W., Landauer, T.K., Gomez, L.M., Dumais, S.T.: The vocabulary problem in human-system communication. Commun. ACM 30(11), 964–971 (1987)
Carpineto, C., Romano, G.: A survey of automatic query expansion in information retrieval. ACM Comput. Surv. 44(1), 1:1–1:50 (2012)
Manning, C.D., Raghavan, P., Schtze, H.: Introduction to Information Retrieval. Cambridge University Press, New York (2008)
Voorhees, E.M.: The cluster hypothesis revisited. In: Proceedings of the 8th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1985, pp. 188–196. ACM, New York (1985)
Leuski, A.: Evaluating document clustering for interactive information retrieval. In: Proceedings of the Tenth International Conference on Information and Knowledge Management, CIKM 2001, pp. 33–40. ACM, New York (2001)
Agirre, E., Arregi, X., Otegi, A.: Document expansion based on wordnet for robust IR. In: Proceedings of the 23rd International Conference on Computational Linguistics: Posters, COLING 2010, pp. 9–17. Association for Computational Linguistics, Stroudsburg (2010)
Kawasaki, S., Nguyen, N.B., Ho, T.B.: Hierarchical document clustering based on tolerance rough set model. In: Zighed, D.A., Komorowski, J., Żytkow, J.M. (eds.) PKDD 2000. LNCS (LNAI), vol. 1910, pp. 458–463. Springer, Heidelberg (2000)
Ho, T.B., Nguyen, N.B.: Nonhierarchical document clustering based on a tolerance rough set model. International Journal of Intelligent Systems 17, 199–212 (2002)
Janusz, A., Świeboda, W., Krasuski, A., Nguyen, H.S.: Interactive document indexing method based on explicit semantic analysis. In: JRS 2012, pp. 156–165 (2012)
Gabrilovich, E., Markovitch, S.: Computing semantic relatedness using wikipedia-based explicit semantic analysis. In: Proceedings of the 20th International Joint Conference on Artificial Intelligence, pp. 1606–1611 (2007)
Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning about Data. Kluwer Academic Publishers (1991)
Skowron, A., Stepaniuk, J.: Tolerance approximation spaces. Fundamenta Informaticae 27(2/3), 245–253 (1996)
Ho, T.B., Kawasaki, S., Nguyen, N.B.: Intelligent exploration of the web, pp. 181–196. Physica-Verlag GmbH, Heidelberg (2003)
Nguyen, H.S., Ho, T.B.: Rough document clustering and the internet. In: Pedrycz, W., Skowron, A., Kreinovich, V. (eds.) Handbook of Granular Computing, pp. 987–1003. John Wiley & Sons, Inc., New York (2008)
Nguyen, S.H., Świeboda, W., Jaśkiewicz, G.: Extended document representation for search result clustering. In: Bembenik, R., Skonieczny, Ł., Rybiński, H., Niezgódka, M. (eds.) Intelligent Tools for Building a Scientific Information Platform. Studies in Computational Intelligence, vol. 390, pp. 77–95. Springer, Heidelberg (2012)
Nguyen, S.H., Świeboda, W., Jaśkiewicz, G., Nguyen, H.S.: Enhancing search results clustering with semantic indexing. In: SoICT 2012, pp. 71–80 (2012)
Nguyen, S.H., Świeboda, W., Jaśkiewicz, G.: Semantic evaluation of search result clustering methods. In: SYNAT 2012, pp. 393–414 (2012)
Virginia, G., Nguyen, H.S.: Lexicon-based document representation. Fundam. Inform. 124(1-2), 27–46 (2013)
United States National Library of Medicine: Introduction to MeSH - 2011 (2011)
Roberts, R.J.: PubMed Central: The GenBank of the published literature. Proceedings of the National Academy of Sciences of the United States of America 98(2), 381–382 (2001)
Miller, G.A.: Wordnet: A lexical database for english. Communications of the ACM 38(1), 39–41 (1995)
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Świeboda, W., Meina, M., Nguyen, H.S. (2013). Weight Learning for Document Tolerance Rough Set Model. In: Lingras, P., Wolski, M., Cornelis, C., Mitra, S., Wasilewski, P. (eds) Rough Sets and Knowledge Technology. RSKT 2013. Lecture Notes in Computer Science(), vol 8171. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41299-8_37
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DOI: https://doi.org/10.1007/978-3-642-41299-8_37
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