Natural Language Processing Technologies for Multi-Level Intelligent Spam Mail-Filter
Haiyan Kang, Xiaojiao Yuan · International Journal of Machine Learning and Computing · 2014
To overcome the lack of existing mail filtering system, we designed a content-based message filtering system of multi-level intelligence.Using natural language processing technology, it denotes the E-mail content including attachments.First, it pre-processes the content of E-mail, including segmentation, feature extraction.Second, combining knowledge-base and expansion of the feature, it can form the vector.Corresponding categories vector in the database, two vectors similar degree of calculation determines the credibility of the message.Based on the above theory, with the Java EE 6+SQL Server 2005 platform, a mail filtering system is achieved.It can maximize the elimination of spam.The major features are following: 1) black /white list filtering.It can intercept white list blacklist e-mail messages released.2) reverse DNS testing. it can effectively eliminate the anonymous e-mail attacks.3) content-based message filtering.An accurate analysis of mail content can filter out suspicious messages.4) fingerprint recognition.It can mimic the biological concept of fingerprint identification to complete the identification of spam.5) user-personalized filtering.The user independently designed filter program.6) intent detection.It can detect the content URL connection in email.Experiment shows mail filter system can play a very good effect on spam filters.