Two-Phase Clustering-based Collaborative Filtering Algorithm
Chen Zhang, Jun Dai, Pei Xian Li, Qing Li, Xubin Luo · 2011
Internet and E-Commerce are becoming an integral part of everyday life as we accumulate more and more knowledge that demands for some personalized recommendation technology. Collaborative filtering recommendation is the most successful personalized recommendation algorithm among current technologies. The paper suggests the two-phase clustering-based collaborative filtering algorithm. which not only reduces the sparsity of data and improves the accuracy of the nearest neighbor, but also improves the recommendation accuracy and reduces the time complexity compared with the traditional algorithms.