{"title":"利用两个单独训练的过滤器的个性化垃圾邮件过滤方法","authors":"W. Teng, W. Teng","doi":"10.1109/WIIAT.2008.257","DOIUrl":null,"url":null,"abstract":"By feeding personal E-mails into the training set, personalized content-based spam filters are believed to classify e-mails in higher accuracy. However, filters trained by both spam mails and personal mails may have difficulty classifying e-mails with the same characteristics of both spam and ham. In this paper, we propose a two-tier approach of using two filters trained only with either personal mails or spam mails. E-mails classified as legitimate mails by the legitimate mail filter may pass, while the remaining e-mails are processed by the spam filter in an ordinary way. Experiments in this paper are performed on two mail servers-one equipped with ordinary spam filter, and the other equipped both the legitimate mail filter and the spam filter. By combining the two filters with tuned thresholds, a much lower false positive rate is observed under the same false negative rate comparing to the ordinary filter.","PeriodicalId":393772,"journal":{"name":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A Personalized Spam Filtering Approach Utilizing Two Separately Trained Filters\",\"authors\":\"W. Teng, W. Teng\",\"doi\":\"10.1109/WIIAT.2008.257\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"By feeding personal E-mails into the training set, personalized content-based spam filters are believed to classify e-mails in higher accuracy. However, filters trained by both spam mails and personal mails may have difficulty classifying e-mails with the same characteristics of both spam and ham. In this paper, we propose a two-tier approach of using two filters trained only with either personal mails or spam mails. E-mails classified as legitimate mails by the legitimate mail filter may pass, while the remaining e-mails are processed by the spam filter in an ordinary way. Experiments in this paper are performed on two mail servers-one equipped with ordinary spam filter, and the other equipped both the legitimate mail filter and the spam filter. By combining the two filters with tuned thresholds, a much lower false positive rate is observed under the same false negative rate comparing to the ordinary filter.\",\"PeriodicalId\":393772,\"journal\":{\"name\":\"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WIIAT.2008.257\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WIIAT.2008.257","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Personalized Spam Filtering Approach Utilizing Two Separately Trained Filters
By feeding personal E-mails into the training set, personalized content-based spam filters are believed to classify e-mails in higher accuracy. However, filters trained by both spam mails and personal mails may have difficulty classifying e-mails with the same characteristics of both spam and ham. In this paper, we propose a two-tier approach of using two filters trained only with either personal mails or spam mails. E-mails classified as legitimate mails by the legitimate mail filter may pass, while the remaining e-mails are processed by the spam filter in an ordinary way. Experiments in this paper are performed on two mail servers-one equipped with ordinary spam filter, and the other equipped both the legitimate mail filter and the spam filter. By combining the two filters with tuned thresholds, a much lower false positive rate is observed under the same false negative rate comparing to the ordinary filter.