C-Rank: A Credibility Evaluation Method for Deep Web Records

Abstract: How to identify and evaluate information credibility ranking has become an increasing important problem. To address the issue, an effective credibility evaluation method called C-Rank to compute trust values of records in Deep Web databases is proposed, which constructs an S-R Credibility Graph for each record. The graph contains 2 types of vertices and 3 types of edges. Firstly, each vertex’s local trust value is computed by using out-degrees based on the idea of trust propagation. Then, the weight of Record vertex is computed by using its in-degree and adjacent Site vertices’ local trust values. Lastly the global trust value of the S-R Credibility Graph is computed, which denotes the record's credibility in the whole Web. Experiment results show C-Rank can evaluate credibility rankings of records appropriatel