A survey of learning-based techniques of email spam filtering

作者:Enrico Blanzieri, Anton Bryl

摘要

Email spam is one of the major problems of the today’s Internet, bringing financial damage to companies and annoying individual users. Among the approaches developed to stop spam, filtering is an important and popular one. In this paper we give an overview of the state of the art of machine learning applications for spam filtering, and of the ways of evaluation and comparison of different filtering methods. We also provide a brief description of other branches of anti-spam protection and discuss the use of various approaches in commercial and non-commercial anti-spam software solutions.

论文关键词:Spam filtering, Machine learning

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论文官网地址:https://doi.org/10.1007/s10462-009-9109-6