January 1, 2009

A New Spam Short Message Classification

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Abstract

This paper proposes an approach of dual-filtering messages. First the combination of KNN classification algorithm and rough set separates spam messages from messages. To avoid lowering precision for reduction, it needs to use KNN classification algorithm to re-filter some messages. This method not only improves the speed of classification but also retains high accuracy based on rough set of KNN classification algorithm.

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Cite This Study

Duan et al. (Thu,) studied this question.

synapsesocial.com/papers/6a11e6cec031bb6829a587d6 https://doi.org/https://doi.org/10.1109/etcs.2009.299

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1A re-examination of text categorization methods1999 · 2,661 citations
2Emotional Agent Based on Rough Set2007 · 3 citations
3Classification of Microarrays with kNN: Comparison of Dimensionality Reduction Methods2007 · 41 citations
4Filtering Short Message Spam of Group Sending Using CAPTCHA2008 · 35 citations
5A Large-Scale Online Spam Short Message Filtering System2008 · 1 citations

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