A bio-inspired approach for multi-word expression extraction

Authors:
Jianyong Duan;Ruzhan Lu;Weilin Wu;Yi Hu;Yan Tian
Affiliations:
Shanghai Jiao Tong University, Shanghai, P.R. China;Shanghai Jiao Tong University, Shanghai, P.R. China;Shanghai Jiao Tong University, Shanghai, P.R. China;Shanghai Jiao Tong University, Shanghai, P.R. China;Shanghai Jiao Tong University, Shanghai, P.R. China
Venue:
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Year:
2006

Citing 13
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Abstract

This paper proposes a new approach for Multi-word Expression (MWE)extraction on the motivation of gene sequence alignment because textual sequence is similar to gene sequence in pattern analysis. Theory of Longest Common Subsequence (LCS) originates from computer science and has been established as affine gap model in Bioinformatics. We perform this developed LCS technique combined with linguistic criteria in MWE extraction. In comparison with traditional n-gram method, which is the major technique for MWE extraction, LCS approach is applied with great efficiency and performance guarantee. Experimental results show that LCS-based approach achieves better results than n-gram.