A Time-Stream Based Method on Spam Filtering
Junyu Niu · Zhongwen xinxi xuebao · 2009
Spam filtering has some characteristics in common with stream data processing,such as high-volume scale,infinite increase and dynamical change.Traditional spam filtering methods use static feature selection approaches which cannot reflect that features of stream data are always dynamically changing as time goes by.In this paper,we propose a spam filtering method based on the characteristics of time stream which can adjust the effective features used for filtering in real time.The experimental results based on TREC spam track corpus show that our method could optimize the temporal and spatial cost of the filtering computation,while keeping the accuracy of the spam filter at a high level.