Breadth-first crawling yields high-quality pages
Proceedings of the 10th international conference on World Wide Web
Spam, damn spam, and statistics: using statistical analysis to locate spam web pages
Proceedings of the 7th International Workshop on the Web and Databases: colocated with ACM SIGMOD/PODS 2004
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Topical TrustRank: using topicality to combat web spam
Proceedings of the 15th international conference on World Wide Web
Detecting spam web pages through content analysis
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
Using spam farm to boost PageRank
AIRWeb '07 Proceedings of the 3rd international workshop on Adversarial information retrieval on the web
A large-scale study of link spam detection by graph algorithms
AIRWeb '07 Proceedings of the 3rd international workshop on Adversarial information retrieval on the web
Combating web spam with trustrank
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Trustworthiness analysis of web search results
ECDL'07 Proceedings of the 11th European conference on Research and Advanced Technology for Digital Libraries
Hi-index | 0.00 |
Since current search engines employ link-based ranking algorithms as an important tool to decide a ranking of sites, Web spammers are making a significant effort to manipulate the link structure of the Web, so called, link spamming. Link hijacking is an indispensable technique for link spamming to bring ranking scores from normal sites to target spam sites. In this paper, we propose a link analysis technique for finding link hijacked sites using modified PageRank algorithms. We performed experiments on the large scale Japanese Web archive and evaluated the accuracy of our method. Detection precision of our approach was improved about 25% from a naive approach.