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Homonym Disambiguation based on Mutual Information and Sense-Tagged Compound Noun Dictionary  

Heo, Jeong (한국전자통신연구원 지식마이닝연구팀)
Seo, Hee-Cheol (한국전자통신연구원 지식마이닝연구팀)
Jang, Myung-Gil (한국전자통신연구원 지식마이닝연구팀)
Publication Information
Journal of KIISE:Software and Applications / v.33, no.12, 2006 , pp. 1073-1089 More about this Journal
Abstract
The goal of Natural Language Processing(NLP) is to make a computer understand a natural language and to deliver the meanings of natural language to humans. Word sense Disambiguation(WSD is a very important technology to achieve the goal of NLP. In this paper, we describe a technology for automatic homonyms disambiguation using both Mutual Information(MI) and a Sense-Tagged Compound Noun Dictionary. Previous research work using word definitions in dictionary suffered from the problem of data sparseness because of the use of exact word matching. Our work overcomes this problem by using MI which is an association measure between words. To reflect language features, the rate of word-pairs with MI values, sense frequency and site of word definitions are used as weights in our system. We constructed a Sense-Tagged Compound Noun Dictionary for high frequency compound nouns and used it to resolve homonym sense disambiguation. Experimental data for testing and evaluating our system is constructed from QA(Question Answering) test data which consisted of about 200 query sentences and answer paragraphs. We performed 4 types of experiments. In case of being used only MI, the result of experiment showed a precision of 65.06%. When we used the weighted values, we achieved a precision of 85.35% and when we used the Sense-Tagged Compound Noun Dictionary, we achieved a precision of 88.82%, respectively.
Keywords
MI; Sense-Tagged Dictionary; Homonym; WSD;
Citations & Related Records
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