A Novel Page Ranking Algorithm Based on Analyzing the Diversity of Inbound Hyperlinks
Bo Yang · Chinese Journal of Computers · 2014
As the core component of a search engine,page ranking algorithm determines in what order the search results should be presented to users and its performance will directly influence search service quality and users' search experience.The existing methods of page ranking and spam detection merely consider the number and the quality of inbound hyperlinks,while ignoring their diversity,another important criterion to objectively evaluate the authority of web pages. Compared with real authority pages,which has a large number inbound hyperlinks from a wide variety of sources,the pages whose ranks are improved by cheating methods often don't have the characteristic of wide diversity of their inbound hyperlinks.Based on aforementioned idea,we propose a method to quantitatively compute the diversity of inbound hyperlinks and a method to adjust the weights of hyperlinks based on it,respectively.Then we propose a novel page rank algorithm,called Drank,which ranks pages based on the diversity analysis of inbound hyperlinks. Our experimental results against several benchmark data sets show that Drank has the best performance in terms of both finding high-quality pages and suppressing web spams.