Improving Pagerank Calculation by using Content Weight

World is full of information. The World Wide Web serves as major source of getting such information. Web plays dynamic role because it contains vast data as collection of large number of webpages and every second new pages are added, updated and deleted in web. Retrieving efficient, relavant and meaningful information from this large source of information is very challanging job. Every search engine applies an algorithm to large number of webpages in search results which calculators rank of every webpages and ensure that most efficient and relevant webpages as per query made by user appear first in search results. In this paper We have analyzed few algorithms which uses link structure or web structure mining and few algorithms which uses web content mining for calculating the pagerank value of webpages and proposed one algorithm which uses both web structure mining as well as web content mining as hybrid for calculating the pagerank value of webpages. Which gives better and efficient results as compare to other and overcome some limitations of web structure mining based algorithms.