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Journal of Information Science and Engineering, Vol. 31 No. 6, pp. 2089-2101 (November 2015)


Word Similarity Computing Based on Hybrid Hierarchical Structure by HowNet*


JINAN XU, JIANGMING LIU AND YUJIE ZHANG
School of Computer Information and Technology
Beijing Jiaotong University
Beijing, 100044 P.R. China
E-mail: {xja2010; jmliunlp}@gmail.com; yjzhang@bjtu.edu.cn

Word similarity computing is one of the most important and fundamental task in the field of natural language processing. Most of word similarity methods perform well in synonyms, but not well between words whose similarity is vague. It confronts the challenge of how to overcome this problem. An approach is proposed to compute Chinese word similarity based on hybrid hierarchical structure by HowNet to achieve fine-grained similarity results. The experimental results prove that the method has a better effect on computing similarity of synonyms and antonyms including nouns, verbs and adjectives. In addition, it performs well and stably on standard data provided by SemEval 2012.

Keywords: word similarity computing, hybrid hierarchical structure, HowNet, concept, WordNet

Full Text () Retrieve PDF document (201511_15.pdf)

Received October 8, 2014; accepted September 30, 2014.
Communicated by Hsin-Min Wang.
* Project 61370130 supported by National Natural Science Foundation of China.