{"title":"网页垃圾邮件:网页语言对垃圾邮件检测特征的影响研究","authors":"A. Alarifi, Mansour Alsaleh","doi":"10.1109/ICMLA.2012.229","DOIUrl":null,"url":null,"abstract":"Although search engines have deployed various techniques to detect and filter out Web spam, Web stammers continue to develop new tactics to influence the result of search engines ranking algorithms, for the purpose of obtaining an undeservedly high ranks. In this paper, we study the effect of the page language on the spam detection features. We examine how the distribution of a set of selected detection features changes according to the page language. Also, we study the effect of the page language on the detection rate of a given classifier using a selected set of detection features. The analysis results show that selecting suitable features for a classifier that segregates spam pages depends heavily on the language of the examined Web page, due in part to the different set of Web spam mechanisms used by each type of stammers.","PeriodicalId":157399,"journal":{"name":"2012 11th International Conference on Machine Learning and Applications","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Web Spam: A Study of the Page Language Effect on the Spam Detection Features\",\"authors\":\"A. Alarifi, Mansour Alsaleh\",\"doi\":\"10.1109/ICMLA.2012.229\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Although search engines have deployed various techniques to detect and filter out Web spam, Web stammers continue to develop new tactics to influence the result of search engines ranking algorithms, for the purpose of obtaining an undeservedly high ranks. In this paper, we study the effect of the page language on the spam detection features. We examine how the distribution of a set of selected detection features changes according to the page language. Also, we study the effect of the page language on the detection rate of a given classifier using a selected set of detection features. The analysis results show that selecting suitable features for a classifier that segregates spam pages depends heavily on the language of the examined Web page, due in part to the different set of Web spam mechanisms used by each type of stammers.\",\"PeriodicalId\":157399,\"journal\":{\"name\":\"2012 11th International Conference on Machine Learning and Applications\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 11th International Conference on Machine Learning and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMLA.2012.229\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 11th International Conference on Machine Learning and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLA.2012.229","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Web Spam: A Study of the Page Language Effect on the Spam Detection Features
Although search engines have deployed various techniques to detect and filter out Web spam, Web stammers continue to develop new tactics to influence the result of search engines ranking algorithms, for the purpose of obtaining an undeservedly high ranks. In this paper, we study the effect of the page language on the spam detection features. We examine how the distribution of a set of selected detection features changes according to the page language. Also, we study the effect of the page language on the detection rate of a given classifier using a selected set of detection features. The analysis results show that selecting suitable features for a classifier that segregates spam pages depends heavily on the language of the examined Web page, due in part to the different set of Web spam mechanisms used by each type of stammers.