An Advance Approach of Page Ranking Using Combination of Web Structure Mining and Web Content Mining

The World Wide Web is popular and interactive medium to propagate information today. The web is huge, diverse, dynamic, widely distributed global information service centre. In the highly competitive world and with the broad use of the web in e-commerce, e-learning and e-news, finding user's need and providing useful information are the primary goals of websites owners. Therefore, analyzing user's patterns of behavior becomes increasingly important. Web mining is used to discover the content of the web, the user's behavior in the past, and the web pages that the users want to view in the future. Web mining is used to categorize users and pages by analyzing the user's behavior, the content of pages, and the order of URLs that tend to be accessed in order. Web structure and web content mining play an important role in this approach. Web content mining is extraction and integration of useful data from web page content. Web Structure Mining deals with hyperlink structure of the web. Most of the users rely on search engine to search the web. But the results returned by the search engine are not mostly relevant to user's query and ranking of pages are not efficient according to users requirement. So In this paper few algorithms which uses link structure or web structure mining and few algorithms which uses web content mining have been analyzed for calculating the page rank value of web page. In order to improve the precision of ranking of the web pages, after analyzing the page rank and its various versions, a new algorithm has been proposed in this paper, which uses both web structure mining as well as web content mining as hybrid for calculating the page rank value of WebPages. This gives better and efficient results as compare to others and overcome some limitations of web structure mining based algorithms.