{"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}
引用次数: 5
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.