Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Proceedings of the 11th international conference on World Wide Web
Valuation of Trust in Open Networks
ESORICS '94 Proceedings of the Third European Symposium on Research in Computer Security
Propagation of trust and distrust
Proceedings of the 13th international conference on World Wide Web
PeerTrust: Supporting Reputation-Based Trust for Peer-to-Peer Electronic Communities
IEEE Transactions on Knowledge and Data Engineering
Identifying link farm spam pages
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Topical TrustRank: using topicality to combat web spam
Proceedings of the 15th international conference on World Wide Web
Link spam detection based on mass estimation
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Computing pagerank in a distributed internet search system
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Combating web spam with trustrank
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Towards robust trust establishment in web-based social networks with socialtrust
Proceedings of the 17th international conference on World Wide Web
Socialtrust: tamper-resilient trust establishment in online communities
Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries
Spam characterization and detection in peer-to-peer file-sharing systems
Proceedings of the 17th ACM conference on Information and knowledge management
Predicting web spam with HTTP session information
Proceedings of the 17th ACM conference on Information and knowledge management
Cost-effective spam detection in p2p file-sharing systems
Proceedings of the 2008 ACM workshop on Large-Scale distributed systems for information retrieval
The SocialTrust framework for trusted social information management: Architecture and algorithms
Information Sciences: an International Journal
Foundations and Trends in Information Retrieval
Augmenting web pages and search results to support credibility assessment
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Survey on web spam detection: principles and algorithms
ACM SIGKDD Explorations Newsletter
Evaluating Arabic spam classifiers using link analysis
Proceedings of the 3rd International Conference on Information and Communication Systems
FindCredPg: a novel method to find credible pages based on trust web graph
APWeb'12 Proceedings of the 14th Asia-Pacific international conference on Web Technologies and Applications
Using site-level connections to estimate link confidence
Journal of the American Society for Information Science and Technology
Web credibility: features exploration and credibility prediction
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
On the subjectivity and bias of web content credibility evaluations
Proceedings of the 22nd international conference on World Wide Web companion
Combating Web spam through trust-distrust propagation with confidence
Pattern Recognition Letters
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We introduce the concept of link credibility, identify the conflation of page quality and link credibility in popular Web link analysis algorithms, and discuss how to decouple link credibility from page quality. Our credibility-based link analysis exhibits three distinct features. First, we develop several techniques for semi-automatically assessing link credibility for all Web pages. Second, our link credibility assignment algorithms allow users to assess credibility in a personalized manner. Third, we develop a novel credibility-based Web ranking algorithm - CredibleRank - which incorporates credibility information directly into the quality assessment of each page on the Web. Our experimental study shows that our approach is significantly and consistently more spam-resilient than both PageRank and TrustRank.