Research of web real-time recommendation model based on mixed
Qiang Ma · Jisuanji gongcheng yu sheji · 2011
Aimed at personalized web site real-time recommendation systems in the past are difficult to predict future user browsing the page,a mixed type real-time recommendation is proposed.The model connects the dynamic fuzzy clustering with improved rules concerned,not only combining both users and page similarity mining weight to form a knowledge base,but also considering the user's access sequence features to configure access mode tree,trimming some related branches to form candidate recommendation set quickly,which is attached to the request page bottom by the recommendation engine,without disturbing the user's access meanwhile recommending the interesting contents to the users.Experiments show that the method can effectively improve the precision and coverage as well as comprehensive evaluation index in the recommendation.