An Improved HITS Algorithm Based on Page-query Similarity and Page Popularity

The HITS algorithm is a very popular and effective algorithm to rank web documents based on the link information among a set of web pages. However, it assigns every link with the same weight. This assumption results in topic drift. In this paper, we firstly define the generalized similarity between a query and a page, and the popularity of a web page. Then we propose a weighted HITS algorithm which differentiates the importance of links with the querypage similarities and the popularity of web pages. Experimental results indicate that the improved HITS algorithm can find more relevant pages than HITS and improve the relevance by 30%-50%. Furthermore, it can avoid the problem of topic drift and enhance the quality of web search effectively.