ID | 118263 |
著者 |
Li, Chao
Tokushima University
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キーワード | Selectional preferences
Distributional semantic model (DSM)
Lexical semantics
Word2vec algorithm
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資料タイプ |
学術雑誌論文
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抄録 | In this paper, we propose a approach based on distributional semantic model to the selectional preference in the verb & dobj (direct object) relationship. The distributional representations of words are employed as the semantic feature by using the Word2Vec algorithm. The machine learning method is used to build the discrimination model. Experimental results show that the proposed approach is effective to discriminate the compatibility of the object words and the performance could be improved by increasing the number of training data. By comparing the previous method, the proposed method obtain the promising results with obvious improvement. Moreover, the results demonstrate that the semantics is an universal, effective and stable feature in this task, which is consistent with our awareness of using words.
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掲載誌名 |
WSEAS Transactions on Computers
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ISSN | 11092750
22242872
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出版者 | World Scientific and Engineering Academy and Society
|
巻 | 15
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開始ページ | 258
|
終了ページ | 264
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発行日 | 2016
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EDB ID | |
出版社版URL | |
フルテキストファイル | |
言語 |
eng
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著者版フラグ |
出版社版
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部局 |
理工学系
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