An Improved Collaborative Filtering Algorithm Based on Combining User with Item
Shi Liu-hong · Computer Knowledge and Technology · 2011
Collaborative Filtering Algorithm is one of the important personalized recommendation technologies,however,as the increasing scale of the ecommerce,the rating matrix is quite sparse.Thus the quality of the approach is seriously deceased.This paper proposes a new improved approach that based on combining user with item by analyzing the deficiency of the traditional algorithm.In this algorithm,we take the information of the users and items into account while predicting the missing data,then build a virtual matrix to recommend the items.The experimental results show that this new approach can efficiently improve the quality of the recommendation.