Active Learning for Online Spam Filtering

摘要：

Spam filtering is defined as a task trying to label emails with spam orham in an online situation.The online feature requires the spam filter has a strong timely generalization and has a high processing speed.Machine learning can be employed to fulfill the two requirements.In this paper,we propose a SVMEL (SVM Ensemble Learning) method to combine five simple filters for higher accuracy and an active learning method to choose training emails for less training time.The experiments results show the filter applying active learning method can reduce requirements of labeled training emails and reach steadystate performance more quickly.

关键词： Spam Filtering Machine Learning Active Learning Ensemble Learning SVM

作者: Wuying Liu Ting Wang

作者单位: School of Computer,National University of Defense Technology No.137,Yanwachi Street,Changsha,Hunan 410073,P.R.China

会议类型: 国际会议

会议名称: 4th Asia Information Retrieval Symposium(AIRS 2008)(第四届亚洲信息检索研讨会)

会议地点: 哈尔滨

会议语种:英文

页码: 555-560

在线出版日期: 2008-01-16（万方平台首次上网日期，不代表论文的发表时间）