A Hybrid Approach to Improve Bilingual Multiword Expression Extraction

Authors:
Jianyong Duan;Mei Zhang;Lijing Tong;Feng Guo
Affiliations:
College of Information Engineering,;College of Art Design, North China University of Technology, Beijing, P.R. China 100141;College of Information Engineering,;College of Information Engineering,
Venue:
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Year:
2009

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Abstract

We propose a hybrid approach for bilingual multiword expression extraction. There are two phases in the extraction process. In the first phase, lots of candidates are extracted from the corpus by statistic methods. The algorithm of multiple sequence alignment is sensitive to the flexible multiword. In the second phase, error-driven rules and patterns are extracted from corpus. These trained rules are used to filter the candidates. Some related experiments are designed for achieving the best performance because there are lots of parameters in this system. Experimental results showed our approach gains good performance.