Personalization Based On Web Log Mining

With the rapid growth of the Internet, users require much better Internet services. Traditional information retrieval technologies satisfy users' need to a great extent. However, for their all-purpose characteristics, they can not satisfy any request from the different background, with the different intention and at the different time. A personalized web site with dynamic modify web site and personalization recommendation system is presented in this paper.Personalization recommendation system is based on the web log mining. It is important for the modern enterprises to have the ability of discovering useful user access pattern and corresponding potential customers from large volume of use access logs, so that they can provide personal information service and make their electronic commerce strategies. With more and more business spread in Internet, The modern enterprises concentrate on the principle of access pattern. It become practical significance and a vastitude foreground to abstract useful knowledge, construct adaptive web site, improve efficiency of WWW with web mining intellectively and automatically.We describe the algorithm and processes of user access pattern, and present a data preprocessing mode. First of all, we take several steps on web log to find users' useful information, such as web site's URL, the time which the user stay on the web site, the times which the user visits the URL and etc. According to these information, we can calculate the users' interests on the page he or she had visited. And the, we would recommend some pages which users haven't visit but maybe favorite to users on the section of Favorite.We present the method of adjusting web page automatic in personalized web site. According to result of web usage mining, the program add dynamic hyperlink automatic by inserting ASP code in web page to present different view to unlike user. And the source program is given. The feasibility of adaptive web sites has been tested by experiments...