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J4  2010, Vol. 44 Issue (4): 732-737    DOI: 10.3785/j.issn.1008-973X.2010.04.019
王瑞琴1,2, 孔繁胜1, 潘俊1
1.浙江大学 人工智能研究所,浙江 杭州310027; 2.温州大学 计算机科学与工程学院,浙江 温州 325035
Unsupervised word sense disambiguation based on WordNet
WANG Ruiqin1,2, KONG Fansheng1, PAN Jun1
1. Institute of Artificial Intelligence, Zhejiang University, Hangzhou 310027, China;
2. School of Computer Science and Engineering, Wenzhou University, Wenzhou 325035, China
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Word sense disambiguation (WSD) based on supervised machine learning is hard to deal with largescale WSD because of its big labor cost. To solve this problem, an unsupervised WSD method was provided, which describes the word senses of an ambiguous word via synthesizing multiple knowledge sources in WordNet ontology, including definition glosses, samples, structured semantic relations, domain attributes, etc. From the description, a representative glossary and a domain representative glossary are deduced. The two structures together with the word sense frequency distribution and the context are used for WSD. The average disambiguation accuracy was 49.93% by this method in open test for six representative unsupervised WSD methods with Senseval3 English lexical sample data set.

出版日期: 2010-05-14
:  TP393  
通讯作者: 孔繁胜,男,教授.     E-mail:
作者简介: 王瑞琴(1979—),女,内蒙古鄂尔多斯人,博士,从事人工智能、语义挖掘研究. E-mail:
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王瑞琴, 孔繁胜, 潘俊. 基于WordNet的无导词义消歧方法[J]. J4, 2010, 44(4): 732-737.

WANG Rui-Qin, KONG Fan-Qing, BO Dun. Unsupervised word sense disambiguation based on WordNet. J4, 2010, 44(4): 732-737.


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