关键词: 深层网络, Web信息可信度, S-R可信度网络, 可信度传播

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 appropriately and discriminate false information effectively. This method is generally applicable to all domains of Deep Web.

Key words: Deep Web, Web information credibility, S-R credibility graph, trust propagation