Abstract
Due to the massive amount of data and information available in web pages, users use search engines to find the desired information from the World Wide Web. Search engines encounter a very challenging task to retrieve relevant information efficiently. When a user inputs the search parameters and keywords into the search engine, there are many web pages that match the user's query. To overcome this challenge, the search engine utilizes ranking algorithm to rank the results. One of the most popular ranking algorithms is the Page Rank algorithm which we consider in this study. One of the challenges related to Page Rank algorithm is that many web pages resulted from the algorithm may not meet the intended search query. So, studies are required to develop and enhance such sort of algorithms including the Page Rank algorithm. This study presents the traditional Page Rank algorithm which focuses on the number of links, Hyperlink-Induced Topic Search algorithms which emphasizes hubs and authorities, and Weighted Page Rank algorithm which weighs in-links and out-links to rank pages. Additionally, it reviews the latest studies that improve page rank algorithms based on user behavior and interest. This study proposes an algorithm called Extended User Preference Based Weighted Page Ranking Algorithm (EUPWPR), which enhances the latest studies of page rank algorithms. Moreover, this study considers more parameters to compute the page rank and the results showed that considering more parameters makes the page rank values more precise.