{"title":"A Statistical Approach to Semantic Analysis for Chinese Terms","authors":"Dongfeng Cai, Na Ye, Guiping Zhang, Yan Song","doi":"10.1109/ICSC.2014.47","DOIUrl":null,"url":null,"abstract":"We propose a statistical semantic analysis method for Chinese terms. We use words, part-of-speech (POS) tags, word distances, word contexts and the first sememe of a word in HowNet as features to train a Support Vector Machine (SVM) model for analyzing term semantics. The model is used to identify dependencies embedded inside a term. A Conditional Random Field (CRF) model is used afterwards to incorporate the dependencies and experimental results showed the effectiveness and validity of our approach.","PeriodicalId":175352,"journal":{"name":"2014 IEEE International Conference on Semantic Computing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Semantic Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSC.2014.47","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We propose a statistical semantic analysis method for Chinese terms. We use words, part-of-speech (POS) tags, word distances, word contexts and the first sememe of a word in HowNet as features to train a Support Vector Machine (SVM) model for analyzing term semantics. The model is used to identify dependencies embedded inside a term. A Conditional Random Field (CRF) model is used afterwards to incorporate the dependencies and experimental results showed the effectiveness and validity of our approach.
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