Research and Design of a Spam Filtering System Based on Probability Inference
Jì Xià · Computer Technology and Development · 2008
Classification is one of the most important research fields in data mining and machine learning.In recent years,there have been extensive studies and rapid progresses in automatic text categorization,which is one of the hotspots and key techniques in information retrieval and data mining field.Designs a spam email filtering system based on improved Bayesian probability inference.It uses weight from probability test to describe the correlativity of data;consequently it solves the inconsistent and mutual independent problems.Applies it to the spam filtering work on Internet,the validity of this system is proved.At last,some future directions of the research are given.