Int J Performability Eng ›› 2018, Vol. 14 ›› Issue (3): 502-511.doi: 10.23940/ijpe.18.03.p11.502511

• Original articles • Previous Articles     Next Articles

An Improved Parallel Collaborative Filtering Algorithm based on Hadoop

Baojun Fu   

  1. Institute of Computer Science and Information Engineering, Harbin Normal University, Harbin, 150025, China


The existed parallel collaborative filtering algorithm based on co-occurrence matrix (CMCF) consumes a lot of time in the construction of co-occurrence matrixes and calculation of matrix multiplication. It also ignores the role of neighboring users, so it will influence the accuracy of recommendation. In order to solve this problem, this paper proposes the improved parallel collaborative filtering algorithm (IPCF) and its implementation on spark. The experimental results show that the improved parallel collaborative filtering algorithm in this paper has better running efficiency and higher recommendation accuracy.

Submitted on December 19, 2017; Revised on January 22, 2018; Accepted on February 17, 2018
References: 14