A Comparison of Concept-base Model and Word Distributed Model as Word Association System

详细信息    查看全文

• 作者：Akihiro Toyoshima^a ; ^{toyoshima.akihiro.su4@is.naist.jp" class="auth_mail" title="E-mail the corresponding author} ; Noriyuki Okumura^b
• 关键词：Concept-base ; Associative words ; Word2Vec ; Concept-dictionary ; Conversation
• 刊名：Procedia Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：96
• 期：Complete
• 页码：385-394
• 全文大小：294 K

文摘

We construct Concept-base based on concept chain model and word vector spaces based on Word2Vec using EDR-electronic- dictionary and Japanese Wikipedia data. This paper describes verification experiments of these models regarding the word association system based on the association-frequency-table. In these experiments, we investigate the tendency using associative words of evaluation basis words obtained by these models. In Concept-base model, we observed a tendency that synonyms, superordinate words, and subordinate words are obtained as associative words. Furthermore we observed a tendency that words, which can be compounds or co-occurrence phrases after connecting headwords of the association-frequency-table, are used as associative words in the Word2Vec model. Moreover evaluation result showed the tendency that associative words mostly have category words in the Word2Vec model.