Personalization recommendation algorithm based on nearest neighbor relation
Hui Li, Yun Hu, Cunhua Li, Xia Wang · Computer Engineering and Applications Journal · 2012
Collaborative filtering is the most successful and widely used recommendation technology in E-commerce recommender systems.However,traditional collaborative filtering algorithm faces severe challenge of sparse user ratings and real-time recommendation.Aiming at the problem of data sparsity for collaborative filtering,a high efficient personalization recommendation algorithm based on nearest neighbor is proposed.The algorithm refines the user ratings data using dimensionality reduction,uses a new similarity measure to find the target users'neighbors,and generates recommendations.The experimental results argue that the algorithm efficiently improves sparsity of rating data,and provides better recommendation results than traditional collaborative filtering algorithms.