直近一年間の累計
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ID 118263
著者
Li, Chao Tokushima University
キーワード
Selectional preferences
Distributional semantic model (DSM)
Lexical semantics
Word2vec algorithm
資料タイプ
学術雑誌論文
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.
掲載誌名
WSEAS Transactions on Computers
ISSN
11092750
22242872
出版者
World Scientific and Engineering Academy and Society
15
開始ページ
258
終了ページ
264
発行日
2016
EDB ID
出版社版URL
フルテキストファイル
言語
eng
著者版フラグ
出版社版
部局
理工学系