Abstract
In this paper we present an approach for effective construction of domain specific thesauri. We assume that the collection is partitioned into document categories. By taking advantage of these pre-defined categories, we are able to conceptualize a new topical language model to weight term topicality more accurately. With the help of information theory, interesting relationships among thesaurus elements are discovered deductively. Based on the “Layer-Seeds” clustering algorithm, topical terms from documents in a certain category will be organized according to their relationships in a tree-like hierarchical structure — a thesaurus. Experimental results show that the thesaurus contains satisfactory structures, although it differs to some extent from a manually created thesaurus. A first evaluation of the thesaurus in a query expansion task yields evidence that an increase of recall can be achieved without loss of precision.
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References
Crouch, C.J., Yang, B.: Experiments in automatic statistical thesaurus construction. In: SIGIR 1992, 15th Int. ACM/SIGIR Conf. on R&D in Information Retrieval, Copenhagen, Denmark, June 1992, pp. 77–87 (1992)
Fuhr, N., Roelleke, T.: HySpirit — A probabilistic inference engine for hypermedia retrieval in large databases. In: International Conference on Extending Database Technology, Valencia, Spain (1998)
Gelbukh, A., Sidorov, G., Guzman-Arenas, A.: Use of a weighted topic hierarchy for document classification. In: Matoušek, V., Mautner, P., Ocelíková, J., Sojka, P. (eds.) TSD 1999. LNCS (LNAI), vol. 1692, p. 133. Springer, Heidelberg (1999)
Jing, Y.F., Croft, W.B.: An Association Thesaurus for Information Retrieval. In: RIAO 94 Conference Proceedings, New York, October 1994, pp. 146–160 (1994)
Lawrie, D.: Language Models for Hierarchical Summarization. Dissertation. University of Massachusetts, Amherst (2003)
Qiu, Y., Frei, H.P.: Concept based query expansion. In: Proceedings of ACM SIGIR International Conference on Research and Development in Information Retrieval, pp. 160–170. ACM Press, New York (1993)
Salton, G.: Automatic Information Organization and Retrieval. McGraw-Hill Book Company, New York (1968)
Sanderson, M., Croft, B.: Deriving concept hierarchies from text. In: The Proceedings of the 22nd ACM SIGIR Conference, pp. 206–213 (1999)
Sparck-Jones, K.: Automatic Keyword Classification for Information Retrieval. Butterworth, London (1971)
Thiel, U., L’Abbate, M., Paradiso, A., Stein, A., Semeraro, G., Abbattista, F., Lops, P.: The COGITO Project. In: e-Business applications: results of applied research on e-Commerce, Supply Chain Management and Extended Enterprises. Section 2: eCommerce, Springer, Heidelberg (2002)
Kilgariff, A.: Thesauruses for Natural Language Processing. Technical Report Series: ITRI- 03-15, ITRI, Univ. of Brighton
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Chen, L., Thiel, U. (2004). Language Modeling for Effective Construction of Domain Specific Thesauri. In: Meziane, F., Métais, E. (eds) Natural Language Processing and Information Systems. NLDB 2004. Lecture Notes in Computer Science, vol 3136. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27779-8_21
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DOI: https://doi.org/10.1007/978-3-540-27779-8_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22564-5
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