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.
Cite
CITATION STYLE
Duan, J., Lu, R., Wu, W., Hu, Y., & Tian, Y. (2006). A bio-inspired approach for multi-word expression extraction. In COLING/ACL 2006 - 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Main Conference Poster Sessions (pp. 176–182). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1273073.1273096
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