The Research Of Personalized Search Based On Improved Pagerank Algorithm

With the development of Internet technology and the growing network of information, network information faces some problem such as large amount of information, information form is confusing and difficult to manage. At present the Internet search engine technology is aimed at matching keywords to search for and not filtering for the search results which are returned, that caused great inconvenience for users to find necessary information and reduced the search efficiency. And as the Internet user experience and interactive increased demand, personalized search become the main direction and trend of search engines research. The user interest model is the core of personalized search technology, the user interest model will have a direct impact on the quality of the personalized search.This paper is based on Google’s famous PageRank ranking algorithm, build a user interest model to study personalized search. The first chapter introduces the background of the subject research situation and significance and some theoretical basis used by this paper; The second chapter basically analysis the technologies used for building user interest model and set up the first frame; The third chapter basically deduces user interest model according to the improvement of the PageRank algorithm; The fourth chapter is basically to design experiment, through the relevant data analysis and calculation to verify the validity of the model; The last chapter is the summary and outlook. This paper focus on analysis and improvement of PageRank algorithm theory, analysis personalized search engine and user navigation behavior, study user interests access method and set up model based on web favorites and browse records. The difficult is to verify validity of user interest model through the relevant data analysis and calculation.