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An Improved Bayesian Algorithm for Filtering Spam E-Mail

机译:一种改进的过滤垃圾邮件的贝叶斯算法

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摘要

With the wide application of E-mail, unsolicited bulk email has become a major problem for E-mail users. In order to reduce the influence of spam false negative result, an improvement solution based on the traditional Bayesian algorithm is proposed, in which the loss factor is introduced to evaluate the risk of spam false negative rate. At last, the experimental result indicates that the improved Bayesian algorithm can reduce the false negative error rate when filtering spam E-mail, and get more desirable recall ratios and precision ratios.
机译:随着电子邮件的广泛应用,未经请求的批量电子邮件已成为电子邮件用户的主要问题。为了降低垃圾邮件假阴性结果的影响,提出了一种基于传统贝叶斯算法的改进解决方案,其中引入了损耗因子来评估垃圾邮件假负率的风险。最后,实验结果表明,在过滤垃圾邮件电子邮件时,改进的贝叶斯算法可以降低假负误差率,并获得更理想的回忆比和精度比率。

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