Noun-Phrase Analysis in Unrestricted Text for Information Retrieval

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dc.creatorEvans, David A.
dc.creatorZhai, Chengxiang
dc.date1996-05-13
dc.date.accessioned2026-07-07T09:10:16Z
dc.date.available2026-07-07T09:10:16Z
dc.descriptionInformation retrieval is an important application area of natural-language processing where one encounters the genuine challenge of processing large quantities of unrestricted natural-language text. This paper reports on the application of a few simple, yet robust and efficient noun-phrase analysis techniques to create better indexing phrases for information retrieval. In particular, we describe a hybrid approach to the extraction of meaningful (continuous or discontinuous) subcompounds from complex noun phrases using both corpus statistics and linguistic heuristics. Results of experiments show that indexing based on such extracted subcompounds improves both recall and precision in an information retrieval system. The noun-phrase analysis techniques are also potentially useful for book indexing and automatic thesaurus extraction.
dc.description8 pages, gzipped, uuencoded Postscript file, to appear in ACL'96
dc.identifierhttps://arxiv.org/abs/cmp-lg/9605019
dc.identifierhttp://arxiv.org/abs/cmp-lg/9605019
dc.identifierProceedings of the 34th Annual Meeting of Association for Computational Linguistics, Santa Cruz, California, June 24-28, 1996. 17-24.
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/151306
dc.subjectComputation and Language
dc.titleNoun-Phrase Analysis in Unrestricted Text for Information Retrieval
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