教授 博士生导师 硕士生导师
性别: 男
毕业院校: 中国科技大学
学位: 博士
所在单位: 软件学院、国际信息与软件学院
学科: 计算机应用技术. 软件工程
电子邮箱: xczhang@dlut.edu.cn
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论文类型: 会议论文
发表时间: 2009-11-02
收录刊物: EI、Scopus
页面范围: 31-38
摘要: Seed sets are of significant importance for trust propagation based anti-spamming algorithms, e.g., TrustRank. Conventional approaches require manual evaluation to construct a seed set, which restricts the seed set to be small in size, since it would cost too much and may even be impossible to construct a very large seed set manually. The small-sized seed set can cause detrimental effect on the final ranking results. Thus, it is desirable to automatically expand an initial seed set to a much larger one. In this paper, we propose the first automatic seed set expansion algorithm (ASE), which expands a small seed set by selecting reputable seeds that are found and guaranteed to be reputable through a joint recommendation link structure. Experimental results on the WEBSPAM-2007 dataset show that with the same manual evaluation efforts, ASE can automatically obtain a large number of reputable seeds with high precision, thus significantly improving the performance of the baseline algorithm in terms of both reputable site promotion and spam site demotion. Copyright 2009 ACM.