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1、ISSN1000-9825,CODENRUXUEWE-mail:jos@iscas.ac.cnJournalofSoftware,Vol.21,No.6,June2010,pp.1287?1295http://www.jos.org.cndoi:10.3724/SP.J.1001.2010.03591Tel/Fax:+86-10-62562563?byInstituteofSoftware,theChineseAcademyofSciences.Allrightsreserved.?基于特征選擇和最大熵模型
2、的漢語詞義消歧1,21,2+何徑舟,王厚峰1(北京大學信息科學技術學院計算語言學研究所,北京100871)2(北京大學計算語言學教育部重點實驗室,北京100871)ChineseWordSenseDisambiguationBasedonMaximumEntropyModelwithFeatureSelection1,21,2+HEJing-Zhou,WANGHou-Feng1(InstituteofComputationalLinguistics,SchoolofElectronicEngineering
3、andComputerScience,PekingUniversity,Beijing100871,China)2(KeyLaboratoryofComputationalLinguistics(MinistryofEducation),PekingUniversity,Beijing100871,China)+Correspondingauthor:E-mail:wanghf@pku.edu.cnHeJZ,WangHF.Chinesewordsensedisambiguationbasedonmaximu
4、mentropymodelwithfeatureselection.JournalofSoftware,2010,21(6):1287?1295.http://www.jos.org.cn/1000-9825/3591.htmAbstract:Wordsensedisambiguation(WSD)canbethoughtasaclassificationproblem.Featureselectionisofgreatimportanceinsuchatask.Ingeneral,featuresares
5、electedmanually,whichrequiresadeepunderstandingofthetaskitselfandtheemployedclassificationmodel.Inthispaper,theeffectoffeaturetemplateonChineseWSDisstudied,andanautomaticfeatureselectionalgorithmbasedonmaximumentropymodel(MEM)isproposed,includinguniformfea
6、turetemplateselectionforallambiguouswordsandcustomizedfeaturetemplateselectionforeachword.ExperimentalresultshowsthatautomaticfeatureselectioncanreducefeaturesizeandimproveChineseWSDperformance.ComparedwiththebestevaluationresultsofSemEval2007:task#5,thism
7、ethodgetsMicroAve(micro-averageaccuracy)increase3.10%andMacroAve(macro-averageaccuracy)2.96%respectively.Keywords:maximumentropymodel;classificationfeature;automaticfeatureselection;Chinesewordsensedisambiguation摘要:詞義消歧是自然語言處理中一類典型的分類問題.在分類中,特征的選擇至關重要.通常情況
8、下,特征是由人工選擇的,這就要求特征選取者對于待分類的問題本身和分類模型的特點有深刻的認識.分析了漢語詞義消岐中特征模板對消歧結果的影響,在此基礎上提出一套基于最大熵分類模型的自動特征選擇方法,包括針對所有歧義詞的統(tǒng)一特征模板選擇和針對單個歧義詞的獨立特征模板優(yōu)化算法.實驗結果表明,使用自動選擇的特征,不僅簡化了特征模板,而且提高了漢語詞義消歧的性能.與SemEval2007:task#5的最好成績相比,該方法分
