意见垃圾邮件检测在Web论坛

Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval Pub Date : 2015-08-09 DOI:10.1145/2766462.2767766

Yu-Ren Chen, Hsin-Hsi Chen

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引用次数: 21

摘要

本文以一个真实的案例研究了网络论坛中垃圾言论者的检测问题。利用RBF核支持向量机(SVM)和频繁项集挖掘技术，对用户的个人资料、用户发帖的最大垃圾性、用户注册的突发性和频繁贴文集进行了研究，建立了支持向量机模型。该模型的精度为0.6753，召回率为0.6190,F1分数为0.6460。结果是有希望的，因为在测试集中意见垃圾邮件制造者的比例只有0.98%。

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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Opinion Spammer Detection in Web Forum

In this paper, a real case study on opinion spammer detection in web forum is presented. We explore user profiles, maximum spamicity of first posts of users, burstiness of registration of user accounts, and frequent poster set to build a model with SVM with RBF kernel and frequent itemset mining. The proposed model achieves 0.6753 precision, 0.6190 recall, and 0.6460 F1 score. The result is promising because the ratio of opinion spammers in the test set is only 0.98%.

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来源期刊

Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval

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