With the remarkable growth of information obtainable to end users through the web, search engines come to play ever a more significant role. The search engines sometimes give disappointing search results for lack of any classification of search. If we can somehow find the preference of user about the search result and rank pages according to that preference, the result will be more accurate to the user. In this paper page ranking algorithm is being proposed based on the notion of query independent constrained ranked retrieval, which, given a query and a time constraint, produces the best possible ranked list within the specified time limit. The proposed algorithm is based on the constraint that makes Query independency feature where keywords are given less weights and the hyperlinks used with time selection decisions are used. We record the visited time of the page using Log files it means we use the time factor to get better precision of the ranking. Experiments on different test collections show that this algorithm is able to satisfy imposed time constraints, and being able to deliver more effective results, especially under tight time constraints. The proposed approach mainly consists of three steps: select some web pages based on user’s demand, measure their damping factor, and give different weightage to each page depending upon how much time user spending on the web page. The results of our simulation studies show that algorithm performs better than the conventional PageRank algorithm in terms of returning larger number of relevant pages to a given query

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