A Model for Mining Related Pages Based on Usage Information in WWW

This paper provided a model for mining related Web pages based on Web usage information. The input to the model is the URL of a page,and the output is a set of related Web pages. The assumption of the model is that if a group of users who have the same interest trend,those pages they have visited are probably related. The model first to find a group of users who have the same interest trend and are most interested in the input page,then to collect those pages in which those users are interested,and at last to mine related pages from those collected pages. Contrast to other popular approaches in searching related Web pages,the model relies on Web usage information. Model claim that human should be the authority to judge what are really related Web pages,and Web usage information can help to make good use of latent human judgment in related pages. Experiments show the model is practicable. The model can be used in relevance feedback in traditional IR,and can also be used to predict related topics in Web content security.