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

机译:概念库模型与词分布模型作为词联想系统的比较

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摘要

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.
机译:我们使用EDR电子词典和日语Wikipedia数据,基于概念链模型和基于Word2Vec的词向量空间构建了基于概念的库。本文描述了基于关联频率表的关于单词关联系统的这些模型的验证实验。在这些实验中,我们使用由这些模型获得的评估基础词的联想词来研究这种趋势。在基于概念的模型中,我们观察到了将同义词,上级词和下级词作为关联词获得的趋势。此外,我们观察到一种趋势,即可以将关联频率表的headwords连接后的复合词或共现词用作Word2Vec模型中的关联词。此外,评估结果表明在Word2Vec模型中联想词大多具有类别词。

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