Extended Weighted Page Rank Based on VOL by Finding User Activities Time and Page Reading Time, Storing them Directly on Search Engine Database Server

International audienceSearching on the web can be considered as a process of user enters the query and search system returns a set of most relevant pages in response to user’s query. But results returned are not mostly relevant to user’s query and ranking of the pages are not efficient according to user requirement. In order to improve the precision of ranking of the web pages, after analyzing the different algorithms like Page Rank, Weighted Page Rank, Page Rank based on VOL, Weighted Page Rank algorithm based on VOL. In this paper, we are proposing enhancement by including “User Activities Time” and “Page Reading Time” in Weighted Page Rank based on VOL algorithm (WPRVOL). Page Reading Time (PRT) is the total time page remains focused in browser tab. User Activities Time (UAT) is the total time user does activities like Key Press, Mouse Click, Touch the Screen and Scrolling the page etc. WPRVOL Algorithm signifies the importance of a web page for a user and thus helps in increasing the accuracy of web page ranking. Our proposed Extended Weighted Page Rank based on Visit of links (EWPRvolT) algorithm is a page ranking mechanism, which considers user browsing behavior / user using trends into account. Other algorithms discussed in literature are either link or content oriented. WPRVOL has already being devised for search engines, which works very much similar to weighted page rank algorithm and takes number of visits of inbound links of web pages into account. Also we are making one more improvement in our algorithm (EWPRvolT) by storing the no of visits on links, PRT and UAT information directly on Search Engine database server instead of storing it on client’s web server in the form of logs which was suggested in earlier literature. The proposed improvement in algorithm finds more relevant information according to user’s query. So, this concept is very useful to display most important and useful pages on the top of the result list on the basis of user usage trends, which reduce the search space to a large scale for user