{"title":"垃圾邮件过滤的改进贝叶斯算法","authors":"Yin Hu, Chaoyang Zhang","doi":"10.1109/IPTC.2011.29","DOIUrl":null,"url":null,"abstract":"With the wide application of E-mail, unsolicited bulk email has become a major problem for E-mail users. In order to reduce the influence of spam false negative result, an improvement solution based on the traditional Bayesian algorithm is proposed, in which the loss factor is introduced to evaluate the risk of spam false negative rate. At last, the experimental result indicates that the improved Bayesian algorithm can reduce the false negative error rate when filtering spam E-mail, and get more desirable recall ratios and precision ratios.","PeriodicalId":178979,"journal":{"name":"International Symposium on Information Processing and Trusted Computing","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"An Improved Bayesian Algorithm for Filtering Spam E-Mail\",\"authors\":\"Yin Hu, Chaoyang Zhang\",\"doi\":\"10.1109/IPTC.2011.29\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the wide application of E-mail, unsolicited bulk email has become a major problem for E-mail users. In order to reduce the influence of spam false negative result, an improvement solution based on the traditional Bayesian algorithm is proposed, in which the loss factor is introduced to evaluate the risk of spam false negative rate. At last, the experimental result indicates that the improved Bayesian algorithm can reduce the false negative error rate when filtering spam E-mail, and get more desirable recall ratios and precision ratios.\",\"PeriodicalId\":178979,\"journal\":{\"name\":\"International Symposium on Information Processing and Trusted Computing\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Symposium on Information Processing and Trusted Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPTC.2011.29\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Information Processing and Trusted Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPTC.2011.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Improved Bayesian Algorithm for Filtering Spam E-Mail
With the wide application of E-mail, unsolicited bulk email has become a major problem for E-mail users. In order to reduce the influence of spam false negative result, an improvement solution based on the traditional Bayesian algorithm is proposed, in which the loss factor is introduced to evaluate the risk of spam false negative rate. At last, the experimental result indicates that the improved Bayesian algorithm can reduce the false negative error rate when filtering spam E-mail, and get more desirable recall ratios and precision ratios.