Effectively Detecting Content Spam on the Web Using Topical Diversity Measures

Recent studies about web spam detection have utilized various content-based and link-based features to construct a spam classification model. In this paper, we conduct a thorough analysis of content spam on the web using topic models and propose several novel topical diversity measures for content s...

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Veröffentlicht in:	2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Jg. 1; S. 266 - 273
Hauptverfasser:	Dong, Cailing, Zhou, Bin
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.12.2012
Schlagworte:	Analytical models Benchmark testing classification Data models Engines Feature extraction personalization Probabilistic logic topic model Training Vocabulary Web pages Web search web spam
ISBN:	9781467360579, 1467360570
Online-Zugang:	Volltext
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