基于在线线性判别学习的垃圾邮件过滤器

2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery Pub Date : 2008-10-18 DOI:10.1109/FSKD.2008.12

Haoliang Qi, Xiaoning He, Muyun Yang, Jun Yu Li, Guohua Lei, Zhong-yuan Han, Sheng Li

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引用次数: 1

摘要

本文描述了一种简单而有效的判别学习算法用于垃圾邮件过滤。在贝叶斯框架内静态导出特征，根据特征的位置进行聚类，并分别赋值权重。用TREC垃圾语料库对模型进行评价，并与TREC结果进行比较。实验结果表明，我们的线性判别模型能够产生竞争结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Online Linear Discriminative Learning for Spam Filter

This paper describes a simple but effective discriminative learner for spam filter. We statically derive the features within Bayesian framework, cluster them into groups according to their position and then assigning weights respectively. The model is evaluated by TREC Spam corpus and compared with the TREC results. Experimental results show that our linear discriminative model can produce competitive results.

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2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery

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