{"title":"基于Naïve贝叶斯方法的中文文本分类器研究与实现","authors":"Jian Huang, Zhongdi Cen, Qiuhong Zheng","doi":"10.1109/SKG.2010.79","DOIUrl":null,"url":null,"abstract":"Naïve Bayes classifier is proved to be one of the most effective classifier an be used widely. It applies statistical theory to text classification. This paper researched and implemented a Chinese text classifier using JAVA base on Naïve Bayes Method. First of all, this paper described test classification system, the content includes text information expressing, extracting and the method of Chinese text classification. Then it used JAVA to implement Naïve Bayes classification algorithm. Finally this paper made a performance evaluation to the classifier in this classification system, it used the indicators of precision, recall and run time to evaluate the classification results, experiment showed that this classification system has a higher classification accuracy.","PeriodicalId":105513,"journal":{"name":"2010 Sixth International Conference on Semantics, Knowledge and Grids","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Research and Implement of Chinese Text Classifier Based on Naïve Bayes Method\",\"authors\":\"Jian Huang, Zhongdi Cen, Qiuhong Zheng\",\"doi\":\"10.1109/SKG.2010.79\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Naïve Bayes classifier is proved to be one of the most effective classifier an be used widely. It applies statistical theory to text classification. This paper researched and implemented a Chinese text classifier using JAVA base on Naïve Bayes Method. First of all, this paper described test classification system, the content includes text information expressing, extracting and the method of Chinese text classification. Then it used JAVA to implement Naïve Bayes classification algorithm. Finally this paper made a performance evaluation to the classifier in this classification system, it used the indicators of precision, recall and run time to evaluate the classification results, experiment showed that this classification system has a higher classification accuracy.\",\"PeriodicalId\":105513,\"journal\":{\"name\":\"2010 Sixth International Conference on Semantics, Knowledge and Grids\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Sixth International Conference on Semantics, Knowledge and Grids\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SKG.2010.79\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Sixth International Conference on Semantics, Knowledge and Grids","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SKG.2010.79","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research and Implement of Chinese Text Classifier Based on Naïve Bayes Method
Naïve Bayes classifier is proved to be one of the most effective classifier an be used widely. It applies statistical theory to text classification. This paper researched and implemented a Chinese text classifier using JAVA base on Naïve Bayes Method. First of all, this paper described test classification system, the content includes text information expressing, extracting and the method of Chinese text classification. Then it used JAVA to implement Naïve Bayes classification algorithm. Finally this paper made a performance evaluation to the classifier in this classification system, it used the indicators of precision, recall and run time to evaluate the classification results, experiment showed that this classification system has a higher classification accuracy.