A Balanced Rank Algorithm Based on PageRank and Page Belief Recommendation
Yongbin Qin, Daoyun Xu · 2010
Web search engines have become one of the absolutely necessary tools for us in the use of the Internet. They are receiving keen appreciation from the broad masses of network users because of the ability of quick search and the navigation service. However, the current used search engines do not take the actual situation and actual need of users into account, users may meet the topic drift problems in the searching process. Based on the PageRank algorithm, taking the human factor into consideration, we introduce page belief recommendation mechanism and bring forward a balanced rank algorithm based on PageRank and page belief recommendation. This algorithm attaches importance into the subjective needs of the users, it can effectively avoid topic drift problems.