User Preference Based Weighted Page Ranking Algorithm

Abstract

Due to the huge number of information on the internet, users use search engines to fetch the relevant pages, which include the information that meet users' needs. Search engines encountered some challenges in the process of retrieving pages matching user queries. To improve search results and how the user navigates the results of pages, search engines applied ranking method on the obtained search results. In this paper, we discussed the main Page Ranking algorithms including PageRank, Weighted Page Rank and Hyperlink- Induced Topic Search algorithms. we presented a comparative study of the latest improvements on the page ranking algorithms focusing on the algorithms that are related to user preference and user behavior. The main contribution of this paper is the proposal of an algorithm called User Preference Based Weighted Page Ranking Algorithm (UPWPR) which is an enhancement for existing ranking algorithms. UPWPR algorithm uses web content mining and web usage mining in order to rank the search results based on user preferences. A numerical case study was used to validate and compare UPWPR proposed algorithm. Results showed better ranking output based on different parameters such as the Content Weight, the User Activities Time, Page Reading Time, and the number of visits.