Improving Accuracy of Spam Detection

作     者：HANI M. O. Iwidat 

作者机构：School of Computer Science and Engineering Beijing University of Aeronautics and Astronautics 

出 版 物：《Computer Aided Drafting,Design and Manufacturing》 (计算机辅助绘图设计与制造（英文版）)

年 卷 期：2008年第18卷第2期

页      码：103-108页

摘      要：Spam, the electronic equivalent of junk mail, affects over 600 million users worldwide. The massive increase of spam is posing a very serious threat to email which has become an important means of communication. Not only does it annoy users, but it also consumes much of the bandwidth of the Internet. Even as anti-spam solutions change to limit the amount of spam sent to users, the senders adapt to make sure their messages are seen, while spam reorganization has different properties comparing with normal text reorganization. Presented are three different classifiers are combined with detailed analysis on various training data set of the given spam database. These classifiers are combined into a mixture of experts (MOE) system which yields overall better performance than any of the individual contributors. The instructions for further improvements on classifiers as well as its requirement on spam databases are also given.

主 题 词：spam mail classification KNN mixture system 

学科分类：08[工学] 080402[080402] 0804[工学-材料学] 

D　O　I：10.19583/j.1003-4951.2008.02.014

馆 藏 号：203857330...