Research for Intelligent and Customized Email Filtering Based on Latent Semantic Indexing and Support Vector Machine
Fangmin Li · Computer Engineering and Applications Journal · 2006
Latent Semantic Indexing(LSI) is an effective method for Information Retrieval(IR),and it also has been successfully applied to text classification.LSI can resolve the problems of polysemy and synonymy,and make the semantic relation between document and term turn more obvious through reducing noise in the raw document-term matrix.In this paper,in order to prevent and filter the unsolicited emails and harmful messages,under multi-languages(Chinese and English) circumstance an improving LSI approach was proposed for customized Email filtering system,Latent Semantic Model was applied to represent the predefined and filtered information categories,Support Vector Machine(SVM) al-gorithm was chosen to recognize and classify predefined and customized unsolicited and harmful information through Singular Value Decomposition(SVD) and positive examples supervised learning.The results of the experiment show that the approach based on LSI and SVM is a more effective approach to information identifying,it not only has a good filtering performance but also can greatly reduce the complexity of computation.