摘要

How to rank Web resources is critical to Web Resource Discovery (Search Engine). This paper not only points out the weakness of current approaches, but also presents in-depth analysis of the multidimensionality and subjectivity of rank algorithms. From a dynamics viewpoint, this paper abstracts a user's Web surfing action as a Markov model. Based on this model, we propose a new rank algorithm. The result of our rank algorithm, which synthesizes the relevance, authority, integrativity and novelty of each Web resource, can be computed efficiently not by iteration bur through solving a group of linear equations.