Abstract
To retrieve relevant information, indexing should be achieved using the concepts of the document that a writer intends to highlight. Moreover, the user involvement is increasingly required to extract relevant information from information sources. Therefore, in the present work we propose a fuzzy retrieval model indexed by concept identification: (1) a concept identification based indexing and (2) a novel fuzzy ranking model. The concept based indexing identifies index terms by considering the concepts of a document, and a novel fuzzy ranking model based on the user preference is presented, which is able to calculates the relevance ranking based on the user preference.
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References
Lee, J.H.: On the evaluation of Boolean operators in the extended boolean retrieval framework. In: Proceedings of the 17th SIGIR conference, pp. 182–190 (1994)
Baeza-Yates, R., et al.: Modern information retrieval. Addison-Wesley, Reading (1999)
Kang, B., Kim, V., Lee, S.: Exploiting concept clusters for content-based information retrieval. Information Sciences 170(2-4), 443–462 (2005)
Hirst, G., St-Onge, D.: Lexical chains as representations of context for the detection and correction of malapropisms. In: Fellbaum, C. (ed.) WordNet: An electronic lexical database, The MIT Press, Cambridge (1998)
Wang, W.J.: New similarity measures on fuzzy sets and on elements. Fuzzy Sets and Systems 85, 305–309 (1997)
Fan, J., Xie, W.: Some notes on similarity measure and proximity measure. Fuzzy Sets and Systems 101, 403–412 (1999)
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Kang, BY., Kim, DW., Kim, HJ. (2005). Fuzzy Information Retrieval Indexed by Concept Identification. In: Matoušek, V., Mautner, P., Pavelka, T. (eds) Text, Speech and Dialogue. TSD 2005. Lecture Notes in Computer Science(), vol 3658. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11551874_23
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DOI: https://doi.org/10.1007/11551874_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28789-6
Online ISBN: 978-3-540-31817-0
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