Research and Improvement of Collaborative Filtering Recommendation Algorithm
Hua Tao Fan · Computer Technology and Development · 2013
The traditional user-based collaborative filtering algorithm calculates users' similarity according to user-item rating matrix,but in real business system,the user-ratings data is very sparse,so the calculation accuracy is very low.The calculation method mixing user similarity and project classification features based similarity is proposed for similarity calculation between users,get target user's close neighbor set,calculate recommended results.The experimental results on the MovieLens data set show that,compared with the Pearson similar collaborative filtering algorithm,the above improved algorithm raises the recommendation quality significantly.