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このアイテムの引用には次の識別子を使用してください: http://hdl.handle.net/10119/5002

タイトル: Combining classifiers for word sense disambiguation based on Dempster-Shafer theory and OWA operators
著者: Le, Anh Cuong
Huynh, Van-Nam
Shimazu, Akira
Nakamori, Yoshiteru
キーワード: Computational linguistics
Classifier combination
Word sense disambiguation
OWA operator
Evidential reasoning
発行日: 2007-11
出版者: Elsevier
誌名: Data & Knowledge Engineering
巻: 63
号: 2
開始ページ: 381
終了ページ: 396
DOI: 10.1016/j.datak.2007.03.013
抄録: In this paper, we discuss a framework for weighted combination of classifiers for word sense disambiguation (WSD). This framework is essentially based on Dempster-Shafer theory of evidence (Shafer, 1976) and ordered weighted averaging (OWA) operators (Yager, 1988). We first determine various kinds of features which could provide complementarily linguistic information for the context, and then combine these sources of information based on Dempster's rule of combination and OWA operators for identifying the meaning of a polysemous word. We experimentally design a set of individual classifiers, each of which corresponds to a distinct representation type of context considered in the WSD literature, and then the discussed combi-nation strategies are tested and compared on English lexical samples of Senseval-2 and Senseval-3.
Rights: NOTICE: This is the author's version of a work accepted for publication by Elsevier. Cuong Anh Le, Van-Nam Huynh, Akira Shimazu and Yoshiteru Nakamori, Data & Knowledge Engineering, 63(2), 2007, 381-396, http://dx.doi.org/10.1016/j.datak.2007.03.013
URI: http://hdl.handle.net/10119/5002
資料タイプ: author
出現コレクション:a10-1. 雑誌掲載論文 (Journal Articles)

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