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Improving effectiveness of mutual information for substantival multiword expression extraction
Zhang, Wen1,3; Yoshida, Taketoshi1; Tang, Xijin2; Ho, Tu-Bao1
2009-10-01
Source PublicationEXPERT SYSTEMS WITH APPLICATIONS
ISSN0957-4174
Volume36Issue:8Pages:10919-10930
AbstractOne of the deficiencies of mutual information is its poor capacity to measure association of words with unsymmetrical co-occurrence, which has large amounts for multi-word expression in texts. Moreover, threshold setting, which is decisive for success of practical implementation of mutual information for multi-word extraction, brings about many parameters to be predefined manually in the process of extracting multiword expressions with different number of individual words. In this paper, we propose a new method as EMICO (Enhanced Mutual Information and Collocation Optimization) to extract substantival multiword expression from text. Specifically, enhanced mutual information is proposed to measure the association of words and collocation optimization is proposed to automatically determine the number of individual words contained in a multiword expression when the multiword expression occurs in a candidate set. Our experiments showed that EMICO significantly improves the performance of substantival multiword expression extraction in comparison with a classic extraction method based on mutual information. (C) 2009 Elsevier Ltd. All rights reserved.
KeywordSubstantival multiword expression Mutual information Enhanced mutual information Collocation optimization EMICO
DOI10.1016/j.eswa.2009.02.026
Language英语
Funding ProjectMinistry of Education, Culture, Sports, Science and Technology of Japan ; National Natural Science Foundation of China[70571078] ; National Natural Science Foundation of China[70221001]
WOS Research AreaComputer Science ; Engineering ; Operations Research & Management Science
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS IDWOS:000267179500016
PublisherPERGAMON-ELSEVIER SCIENCE LTD
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/8564
Collection系统科学研究所
Corresponding AuthorZhang, Wen
Affiliation1.Japan Adv Inst Sci & Technol, Sch Knowledge Sci, Ishikari, Hokkaido 9231292, Japan
2.Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, Beijing 100080, Peoples R China
3.Chinese Acad Sci, Inst Software, Lab Internet Software Technol, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Wen,Yoshida, Taketoshi,Tang, Xijin,et al. Improving effectiveness of mutual information for substantival multiword expression extraction[J]. EXPERT SYSTEMS WITH APPLICATIONS,2009,36(8):10919-10930.
APA Zhang, Wen,Yoshida, Taketoshi,Tang, Xijin,&Ho, Tu-Bao.(2009).Improving effectiveness of mutual information for substantival multiword expression extraction.EXPERT SYSTEMS WITH APPLICATIONS,36(8),10919-10930.
MLA Zhang, Wen,et al."Improving effectiveness of mutual information for substantival multiword expression extraction".EXPERT SYSTEMS WITH APPLICATIONS 36.8(2009):10919-10930.
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