The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
ACM Transactions on Internet Technology (TOIT)
Modifications of Kleinberg's HITS algorithm using matrix exponentiation and web log records
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Local versus global link information in the Web
ACM Transactions on Information Systems (TOIS)
Anchor Text Mining for Translation of Web Queries
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Using PageRank to Characterize Web Structure
COCOON '02 Proceedings of the 8th Annual International Conference on Computing and Combinatorics
IEEE Transactions on Knowledge and Data Engineering
Topic-Sensitive PageRank: A Context-Sensitive Ranking Algorithm for Web Search
IEEE Transactions on Knowledge and Data Engineering
THESUS: Organizing Web document collections based on link semantics
The VLDB Journal — The International Journal 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
Applying recursion to serial and parallel QR factorization leads to better performance
IBM Journal of Research and Development
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In this paper, we present a link oriented measuring method to discriminate the manipulated web pages effectively. We define the label of an edge as having a link context and a similarity measure between link context and target page. By suggesting an assessing measure based on singular value decomposition, it is explained that our proposed method can effectively detect the manipulated web pages. We, however, extend the SVD as an assessment measure to detect the rank-manipulated pages. In the experiment, the LOD method reduced about 17% amount of the rank that is minimum 209.4% higher than not manipulated web pages. Using this proposed approach, the chance of manipulated web pages getting high ranks than deserved can be discriminated effectively.