{"title":"Maximum Entropy combined FSM stemming method for Uyghur","authors":"Aishan Wumaier, Zaokere Kadeer, Parida Tursun, Shengwei Tian","doi":"10.1109/ICSDA.2009.5278378","DOIUrl":null,"url":null,"abstract":"This paper presents the generation of Uyghur Noun Suffix DFA combined with Maximum Entropy (MaxEnt) for stemming algorithm. Because of the agglutinative nature of Uyghur language, stemming is an essential task for Uyghur language processing applications. We generate Uyghur noun inflectional suffixes finite state machines (FSMs) by using the morphotactic rules in reverse order. But there are eight suffixes which is similar to the ending part of some words. These suffixes make the FSM ambiguous. We apply the MaxEnt model to resolve ambiguity of the FSM. This paper describes the steps of generating the FSM, building the MaxEnt suffix identifying model and combination of MaxEnt with FSM.","PeriodicalId":254906,"journal":{"name":"2009 Oriental COCOSDA International Conference on Speech Database and Assessments","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Oriental COCOSDA International Conference on Speech Database and Assessments","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSDA.2009.5278378","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper presents the generation of Uyghur Noun Suffix DFA combined with Maximum Entropy (MaxEnt) for stemming algorithm. Because of the agglutinative nature of Uyghur language, stemming is an essential task for Uyghur language processing applications. We generate Uyghur noun inflectional suffixes finite state machines (FSMs) by using the morphotactic rules in reverse order. But there are eight suffixes which is similar to the ending part of some words. These suffixes make the FSM ambiguous. We apply the MaxEnt model to resolve ambiguity of the FSM. This paper describes the steps of generating the FSM, building the MaxEnt suffix identifying model and combination of MaxEnt with FSM.
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