Proceedings Article10.1145/1367497.1367645
User behavior oriented web spam detection
Yiqun Liu,Min Zhang,Shaoping Ma,Liyun Ru +3 more
- 21 Apr 2008
- pp 1039-1040
TL;DR: Preliminary experiments on Web access data collected by a commercial Web site show the effectiveness of the proposed spam page detection algorithm based on Bayes learning.
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Abstract: Combating Web spam has become one of the top challenges for Web search engines State-of-the-art spam detection techniques are usually designed for specific known types of Web spam and are incapable and inefficient for recently-appeared spam With user behavior analyses into Web access logs, we propose a spam page detection algorithm based on Bayes learning Preliminary experiments on Web access data collected by a commercial Web site (containing over 274 billion user clicks in 2 months) show the effectiveness of the proposed detection framework and algorithm
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Citations
FakeDetector: Effective Fake News Detection with Deep Diffusive Neural Network
Jiawei Zhang,Bowen Dong,Philip S. Yu +2 more
- 20 Apr 2020
TL;DR: This paper introduces a novel gated graph neural network, namely FAKEDETECTOR, which builds a deep diffusive network model to learn the representations of news articles, creators and subjects simultaneously.
266
•Posted Content
FAKEDETECTOR: Effective Fake News Detection with Deep Diffusive Neural Network
TL;DR: Li et al. as mentioned in this paper proposed a fake news credibility inference model based on a set of explicit and latent features extracted from the textual information, which can learn the representations of news articles, creators and subjects simultaneously.
54
Analysis and detection of low quality information in social networks
De Wang
- 19 May 2014
TL;DR: This thesis work introduces social spam analytics and detection framework SPADE across multiple social networks showing the efficiency and flexibility of cross-domain classification and associative classification and provides activity-based detection approaches to filter out low quality information in social networks.
29
SPADE: a social-spam analytics and detection framework
De Wang,Danesh Irani,Calton Pu +2 more
TL;DR: The proposed framework SPADE has numerous benefits including accuracy of spam detection will be improved through cross-domain classification and associative classification; other techniques can be integrated and centralized; and new social networks can plug into the system easily, preventing spam at an early stage.
27
Web spam detection using trust and distrust-based ant colony optimization learning
TL;DR: A machine learning approach for solving the problem of Web spam detection based on an adoption of the ant colony optimization (ACO) is proposed to construct rule-based classifiers to distinguish between non-spam and spam hosts.
7
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TL;DR: This paper proposes techniques to semi-automatically separate reputable, good pages from spam, and shows that they can effectively filter out spam from a significant fraction of the web, based on a good seed set of less than 200 sites.
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Zoltan Gyongyi,Hector Garcia-Molina +1 more
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TL;DR: This paper presents a comprehensive taxonomy of current spamming techniques, which it is believed can help in developing appropriate countermeasures.
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Alexandros Ntoulas,Marc Najork,Mark S. Manasse,Dennis Fetterly +3 more
- 23 May 2006
TL;DR: Some previously-undescribed techniques for automatically detecting spam pages are considered, and the effectiveness of these techniques in isolation and when aggregated using classification algorithms is examined.
Analysis of a very large web search engine query log
Craig Silverstein,Hannes Marais,Monika Henzinger,Michael Moricz +3 more
- 01 Sep 1999
TL;DR: It is shown that web users type in short queries, mostly look at the first 10 results only, and seldom modify the query, suggesting that traditional information retrieval techniques may not work well for answering web search requests.
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