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.