Corpus-based approach for building semantic lexicons

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Publication Type Journal Article
School or College College of Engineering
Department Computing, School of
Creator Riloff, Ellen M.
Other Author Shepherd, Jessica
Title Corpus-based approach for building semantic lexicons
Date 1997
Description Semantic knowledge can be a great asset to natural language processing systems, but it is usually hand-coded for each application. Although some semantic information is available in general-purpose knowledge bases such as Word Net and Cyc, many applications require domain-specific lexicons that represent words and categories for a particular topic. In this paper, we present a corpus-based method that can be used t o build semantic lexicons for specific categories. The input t o the system is a small set of seed words for a category and a representative text corpus. The output is a ranked list of words that are associated with the category. A user then reviews the top-ranked words and decides which ones should be entered in the semantic lexicon. Tn experiments with five categories, users typically found about 60 words per category in 10-15 minutes to build a core semantic lexicon.
Type Text
Publisher Association for Computational Linguistics
First Page 1
Last Page 8
Subject Corpus-based method; Semantic lexicons
Subject LCSH Information retrieval; Programming languages (Electronic computers) -- Semantics; Corpora (Linguistics); Natural language processing (Computer science)
Language eng
Bibliographic Citation Riloff, E. M., & Shepherd, J. (1997). Corpus-based approach for building semantic lexicons. Proceedings of the Second Conference on Empirical Methods in Natural Language Processing (EMNLP-2), 1-8.
Rights Management (c) Riloff, E. M., & Shepherd, J.
Format Medium application/pdf
Format Extent 1,063,875 bytes
Identifier ir-main,12425
ARK ark:/87278/s6ng581w
Setname ir_uspace
ID 704980
Reference URL https://collections.lib.utah.edu/ark:/87278/s6ng581w