一个大规模垃圾短信实时过滤系统  

A Large-Scale Online Spam Short Message Filtering System

作　　者：黄文良[1] 李石坚[1] 刘菊新[1] 徐从富[1] 

机构地区：[1]浙江大学计算机学院

出　　处：《北京邮电大学学报》2008年第3期33-37,共5页Journal of Beijing University of Posts and Telecommunications

基　　金：国家“863计划”项目(2007AA01Z197);国家自然科学基金项目(60402010)

摘　　要：在分析现有短信监控系统不足的基础上,结合文本分类技术和行为识别技术,设计了一种垃圾短信监控和过滤系统.系统综合考虑短信发送行为特征、短信文本内容等特点,并采用实时分类和离线分类相结合的方法进行高效短信过滤.此外,还设计了一组基于反馈的自学习机制,使分类器具备增量式学习能力.与传统方法相比,该方法在过滤效率和准确率两方面均获得大幅度提升.It＇s well known that the spam-short-messages are annoying cell-phone users and mobile service providers everyday, A new spam-short-messages filtering system, combining online filtering with offline classifying, is presented. The system can filter messages efficiently according to the sending behavior characteristics and the messages contents, Additionally, a self-learning mechanism is designed based on its operators＇ feedback. It enables the classifiers of the system to improve themselves according to the filtering results, Compared with traditional methods, the presented method has better performance in terms of filtering efficiency and accuracy.

关 键 词：垃圾短信过滤 统计学习 文本分类 

分 类 号：TP319[自动化与计算机技术—计算机软件与理论]