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 query-page 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.