Research On Optimization Of Search Engine Based On PageRank Algorithm

Recently,along with the quick popularization and development of the Internet and Web technology ,it supplies people with abundant information .But the vast Complicated and dynamic Internet information also make it very difficult for people to mine the web resource. So it is a very important method to implement web data mining by combining traditional data mining technology and web.By studying the classical Web structure mining algoritm PageRank,we analyzes the idea and calculating method of the algorithm,establishes different models and advances related optimizing strategies. for the PageRank algorithm only considers the hyperlink between the pages and ignore the content in the pages which come forth the topic draft and other limitations.So a new PageRank algorithm based on hyperlink analyze and content related is proposed. This algorithm analyzes each content in the pages and distributes different weight to improve the PageRank algorithm,and an experiment was set up to analyze the performance and validity of this algorithm.Finally,for the algorithm PageRank will separate the page's authority from the page's hub or even ignore the page's hub, we discuss the personalized PageRank vector and the new algorithm based on PageRank.And the experiment finally prove the improved algorithm is effective to the problem.