WSEAS Transactions on Computers
Print ISSN: 1109-2750, E-ISSN: 2224-2872
Volume 15, 2016
Selectional Preferences Based on Distributional Semantic Model
Authors: , ,
Abstract: 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 theWord2Vec 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.
Search Articles
Keywords: Selectional preferences, Distributional semantic model (DSM), Lexical semantics, Word2vec algorithm
Pages: 258-264
WSEAS Transactions on Computers, ISSN / E-ISSN: 1109-2750 / 2224-2872, Volume 15, 2016, Art. #24