Bagging eEP-based Classifiers for Junk Mail Classification

The volume of junk emails on the Internet has grown tremendously in the past few years and is causing serious problems. Content-based filtering is one of mainstream technologies used so far. This paper has had a deep study in the content of emails and come up with a better idea to get the features which make it even convenient to e-mail classify as well. This paper uses the classification algorithm by Bagging eEP-based classifiers to the junk email examine, and carries out a new categorization and filtering algorithm BeEPJMC. The experiments show, the new feature extraction methods and the combination BeEP classification is a very efficient method of classification, and The classification efficiency of the algorithm BeEPJMC is higher than currently several better classification algorithm.