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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/10119/9212
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| ダブリン･コア･フィールド | 値 | 言語 |
|---|
| contributor.author | Zhang, Wen | en_US |
| contributor.author | Yoshida, Taketoshi | en_US |
| contributor.author | Tang, Xijin | en_US |
| contributor.author | Ho, Tu Bao | en_US |
| date.accessioned | 2010-10-25T06:56:04Z | - |
| date.available | 2010-10-25T06:56:04Z | - |
| date.issued | 2009-02-20 | en_US |
| identifier.uri | http://hdl.handle.net/10119/9212 | - |
| description.abstract | One of the deficiencies of mutual information is its poor capacity to measure association of words with unsymmetrical co-occurrence, which has large amounts for multi-word expression in texts. Moreover, threshold setting, which is decisive for success of practical implementation of mutual information for multi-word extraction, brings about many parameters to be predefined manually in the process of extracting multiword expressions with different number of individual words. In this paper, we propose a new method as EMICO (Enhanced Mutual Information and Collocation Optimization) to extract substantival multiword expression from text. Specifically, enhanced mutual information is proposed to measure the association of words and collocation optimization is proposed to automatically determine the number of individual words contained in a multiword expression when the multiword expression occurs in a candidate set. Our experiments showed that EMICO significantly improves the performance of substantival multiword expression extraction in comparison with a classic extraction method based on mutual information. | en_US |
| format.extent | 558947 bytes | - |
| format.mimetype | application/pdf | - |
| language.iso | en | en_US |
| publisher | Elsevier | en_US |
| rights | NOTICE: This is the author's version of a work accepted for publication by Elsevier. Wen Zhang, Taketoshi Yoshida, Xijin Tang, and Tu-Bao Ho, Expert Systems with Applications, 36(8), 2009, 10919-10930, http://dx.doi.org/10.1016/j.eswa.2009.02.026 | en_US |
| subject | Substantival multiword expression | en_US |
| subject | Mutual information | en_US |
| subject | Enhanced mutual information | en_US |
| subject | Collocation optimization | en_US |
| subject | EMICO | en_US |
| title | Improving effectiveness of mutual information for substantival multiword expression extraction | en_US |
| type.nii | Journal Article | en_US |
| identifier.niiissn | 0957-4174 | en_US |
| identifier.jtitle | Expert Systems with Applications | en_US |
| identifier.volume | 36 | en_US |
| identifier.issue | 8 | en_US |
| identifier.spage | 10919 | en_US |
| identifier.epage | 10930 | en_US |
| relation.doi | 10.1016/j.eswa.2009.02.026 | en_US |
| rights.textversion | author | en_US |
| language.iso639-2 | eng | en_US |
| 出現コレクション: | a10-1. 雑誌掲載論文 (Journal Articles)
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このアイテムのファイル:
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| 13876.pdf | | 545Kb | Adobe PDF | 見る/開く |
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