{"title":"基于BP和isommap的垃圾邮件分类算法","authors":"C. Yu, Wanli Feng, Lei Zhou, Jin Ding","doi":"10.1109/CSQRWC.2013.6657431","DOIUrl":null,"url":null,"abstract":"In this paper, a classification algorithm for spam messages by using the neural network is proposed. First, the spam messages are pretreated, including word separation, feature word extraction, representation with feature word, and formation of text matrix. Then, the dimensionality of the text matrix is reduced by using isomap algorithm. Finally, the classification is achieved by the BP neural network. According to the experimental results, the algorithm gives good classification results.","PeriodicalId":355180,"journal":{"name":"2013 Cross Strait Quad-Regional Radio Science and Wireless Technology Conference","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spam messages classification algorithm based on BP and isomap\",\"authors\":\"C. Yu, Wanli Feng, Lei Zhou, Jin Ding\",\"doi\":\"10.1109/CSQRWC.2013.6657431\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a classification algorithm for spam messages by using the neural network is proposed. First, the spam messages are pretreated, including word separation, feature word extraction, representation with feature word, and formation of text matrix. Then, the dimensionality of the text matrix is reduced by using isomap algorithm. Finally, the classification is achieved by the BP neural network. According to the experimental results, the algorithm gives good classification results.\",\"PeriodicalId\":355180,\"journal\":{\"name\":\"2013 Cross Strait Quad-Regional Radio Science and Wireless Technology Conference\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Cross Strait Quad-Regional Radio Science and Wireless Technology Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSQRWC.2013.6657431\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Cross Strait Quad-Regional Radio Science and Wireless Technology Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSQRWC.2013.6657431","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spam messages classification algorithm based on BP and isomap
In this paper, a classification algorithm for spam messages by using the neural network is proposed. First, the spam messages are pretreated, including word separation, feature word extraction, representation with feature word, and formation of text matrix. Then, the dimensionality of the text matrix is reduced by using isomap algorithm. Finally, the classification is achieved by the BP neural network. According to the experimental results, the algorithm gives good classification results.