NDLI: Web-Based Variant of the Lesk Approach to Word Sense Disambiguation

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Web-Based Variant of the Lesk Approach to Word Sense Disambiguation

Content Provider	IEEE Xplore Digital Library
Author	Gaona, M.A.R. Gelbukh, A. Bandyopadhyay, S.
Copyright Year	2009
Abstract	Word Sense Disambiguation (WSD) is the task of selecting the meaning of a word based on the context in which the word occurs. The principal statistical WSD approaches are supervised and unsupervised learning. The Lesk method is an example of unsupervised disambiguation. We present a measure for sense assignment useful for the simple Lesk algorithm. We use word co-occurrences of the gloss and the context, which is statistical information retrieved from the Web. In the SemCor data our method always gives an answer. On the Senseval 2 data, our variant of the Lesk method outperformed some other Lesk-based methods.
Starting Page	103
Ending Page	107
File Size	248272
Page Count	5
File Format	PDF
ISBN	9780769539331
DOI	10.1109/MICAI.2009.41
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-11-09
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Dictionaries Costs Knowledge acquisition Natural Language Processing Information retrieval Unsupervised learning Computer science Cities and towns Word Sense Disambiguation Mice Artificial intelligence Testing Unsupervised disambiguation
Content Type	Text
Resource Type	Article

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