Journal of Beijing University of Posts and Telecommunications

  • EI核心期刊

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2016, Vol. 39 ›› Issue (s1): 37-41.doi: 10.13190/j.jbupt.2016.s.009

• Papers • Previous Articles     Next Articles

Design and Implementation of Parallel UCSLIM Algorithm Based on Spark

YANG Juan, ZHANG Peng-ye   

  1. Key Laboratory of Intelligent Telecommunication Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2015-09-17 Online:2016-06-28 Published:2016-06-28

Abstract:

A top-N recommendation method-user class sparse linear methods (UCSLIM) based on sparse linear method (SLIM) was proposed. In order to improve the quality of recommendation, we learn from the idea of SLIM algorithm and collaborative filtering algorithm. The users are divided into different sets. So the correlation was analyzed between the user and the set of users and the correlation between user and user. Based on these two factors, UCSLIM was proposed. Experiments show that, compared with SLIM , UCSLIM can improve the quality of results. Furthermore, in order to improve the computational efficiency, the UCSLIM in Hadoop and Spark was implemented. Experiments show that the implementation by Spark has higher efficiency than that of Hadoop.

Key words: TopN recommender system, user class sparse linear methods, user class, Spark

CLC Number: