{"title":"基于对数线性模型的简体繁体汉字转换模型","authors":"Yidong Chen, X. Shi, Changle Zhou","doi":"10.1109/IALP.2011.15","DOIUrl":null,"url":null,"abstract":"With the growth of exchange activities between four regions of cross strait, the problem to correctly convert between Traditional Chinese (TC) and Simplified Chinese (SC) become more and more important. Numerous one-to-many mappings and term usage differences make it more difficult to convert from SC to TC. This paper proposed a novel simplified-traditional Chinese character conversion model based on log-linear models, in which features such as language models and lexical semantic consistency weighs are integrated. When estimating lexical semantic consistency weighs, cross-language word-based semantic spaces were used. Experiments were conducted and the results show that the proposed model achieve better performance.","PeriodicalId":297167,"journal":{"name":"2011 International Conference on Asian Language Processing","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Simplified-Traditional Chinese Character Conversion Model Based on Log-Linear Models\",\"authors\":\"Yidong Chen, X. Shi, Changle Zhou\",\"doi\":\"10.1109/IALP.2011.15\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the growth of exchange activities between four regions of cross strait, the problem to correctly convert between Traditional Chinese (TC) and Simplified Chinese (SC) become more and more important. Numerous one-to-many mappings and term usage differences make it more difficult to convert from SC to TC. This paper proposed a novel simplified-traditional Chinese character conversion model based on log-linear models, in which features such as language models and lexical semantic consistency weighs are integrated. When estimating lexical semantic consistency weighs, cross-language word-based semantic spaces were used. Experiments were conducted and the results show that the proposed model achieve better performance.\",\"PeriodicalId\":297167,\"journal\":{\"name\":\"2011 International Conference on Asian Language Processing\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Asian Language Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IALP.2011.15\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Asian Language Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IALP.2011.15","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Simplified-Traditional Chinese Character Conversion Model Based on Log-Linear Models
With the growth of exchange activities between four regions of cross strait, the problem to correctly convert between Traditional Chinese (TC) and Simplified Chinese (SC) become more and more important. Numerous one-to-many mappings and term usage differences make it more difficult to convert from SC to TC. This paper proposed a novel simplified-traditional Chinese character conversion model based on log-linear models, in which features such as language models and lexical semantic consistency weighs are integrated. When estimating lexical semantic consistency weighs, cross-language word-based semantic spaces were used. Experiments were conducted and the results show that the proposed model achieve better performance.