¹School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China
²Technology & Research Center of Gansu Manufacturing Informatization Engineering, Lanzhou, China

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Abstract—The effect of spam filtering method based on statistics is not good enough in filtering the new-type spam with synonymous substitution and camouflage, because the method based on statistics ignores the semantic relation between words in the text, and only judges from the word itself. So, a method of spam filtering based on the semantic body is proposed in this paper. The method adopts lexical chain based on HowNet and TFIDF method based on statistics to extract e-mail features, and handle spam with text clustering method. The result of the experiment shows that the new method proposed in this pager provides a good effect in filtering new-type spam.

Index Terms—Semantic body, lexical chain, semantic similarity, text clustering, spam filter

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Cite: Qiu-yu Zhang, Peng Wang and Hui-juan Yang, "Applications of Text Clustering Based on Semantic Body for Chinese Spam Filtering," Journal of Computers vol. 7, no. 11, pp. 2612-2616, 2012.