Chinese Word Similarity Computing Based on Combination Strategy

摘要：

　　Chinese word similarity computing is a fundamental task for natural language processing.This paper presents a method to calculate the similarity between Chinese words based on combination strategy.We apply Baidubaike to train Word2Vector model,and then integrate different methods,Dictionary-based method,Word2Vector-based method and Chinese FrameNet(CFN)-based method,to calculate the semantic similarity between Chinese words.The semantic Dictionary-based method includes dictionaries such as HowNet,DaCilin,Tongyici Cilin(Extended)and Antonym.The experiments are performed on 500 pairs of words and the Spearman correlation coefficient of test data is 0.524,which shows that the proposed method is feasible and effective.

关键词： Chinese Word Similarity Computing Combination Strategy Semantic Dictionary Word2Vector Chinese FrameNet

作者: Shaoru GUO Yong GUAN Ru LI Qi ZHANG

作者单位: School of Computer and Information Technology,Shanxi University,Taiyuan,China School of Computer and Information Technology,Shanxi University,Taiyuan,China;Key Laboratory of Mini College of Mathematics and Computer Science,Fuzhou University,Fujian

会议类型: 国际会议

会议名称: 第五届自然语言处理与中文计算会议(NLPCC-ICCPOL2016)

会议地点: 昆明

会议语种:英文

页码: 1-9

在线出版日期: 2016-12-02（万方平台首次上网日期，不代表论文的发表时间）