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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
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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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