Optimized collaborative filtering recommendation based on users' interest degree and feature
Chenghua Lu · Jisuanji yingyong yanjiu · 2012
Collaborative filtering technology is widely used in personalized recommendation system.In order to make the user's nearest neighbors set more precise and effective,this paper presented an optimized collaborative filtering recommendation algorithm based on users' interest degree and feature.Firstly,it grouped users through calculating users' interest degree to items.Secondly,it got the value of the users' preferences for items when the users had different characteristics.Finally,it used a new method of calculating the similarity degree to calculate the target users' nearest neighbors set.The result shows that the algorithm enhances the effectiveness and accuracy of the nearest neighbors set,and the recommendation quality has significant improvement than traditional algorithm.