电子邮件话语的性别偏好文本挖掘

18th Annual Computer Security Applications Conference, 2002. Proceedings. Pub Date : 2002-12-09 DOI:10.1109/CSAC.2002.1176299

M. Corney, O. Vel, Alison Anderson, G. Mohay

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引用次数: 195

摘要

本文研究了一种基于电子邮件文本文档的作者性别归属挖掘方法。我们使用了一组扩展的主要主题内容无关的电子邮件文档特征，如样式标记、结构特征和性别偏好语言特征，以及支持向量机器学习算法。使用由大量男女作者生成的电子邮件文档语料库进行的实验在作者性别分类方面取得了令人鼓舞的结果。

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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Gender-preferential text mining of e-mail discourse

This paper describes an investigation of authorship gender attribution mining from e-mail text documents. We used an extended set of predominantly topic content-free e-mail document features such as style markers, structural characteristics and gender-preferential language features together with a support vector machine learning algorithm. Experiments using a corpus of e-mail documents generated by a large number of authors of both genders gave promising results for author gender categorisation.

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18th Annual Computer Security Applications Conference, 2002. Proceedings.

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