Collaborative Filtering Algorithm Based on Rating Matrix Pre-filling

When the magnitudes of users and commodities grow rapidly,the rating matrix becomes extremely sparse.In the condition,algorithms based on traditional similarity computing have poor performance.In order to overcome this problem,this paper proposes a comprehensive item similarity measurement algorithm based on weighted Jaccard index,and prefills the rating matrix by the comprehensive item similarity.Experimental results show that the algorithm is more accurate compared with traditional algorithms.