• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2015, Vol. 37 ›› Issue (01): 179-183.

• 论文 • Previous Articles     Next Articles

Collaborative filtering algorithm based on
user demographics and expert opinions 

JIAO Dongjun   

  1. (Beijing Key Laboratory of Intelligent Telecommunications,
    Beijing University of Posts and Telecommunications,Beijing 100876,China)
  • Received:2014-09-13 Revised:2014-11-16 Online:2015-01-25 Published:2015-01-25

Abstract:

Recommender systems have been used tremendously in academia and industry, and the recommendations generated by these systems aim to offer relevant interesting items to users. Collaborative filtering algorithm is used to calculate the similarities between users and items, and recommends the nearest neighbors’ preferences to users. In order to improve the prediction accuracy of collaborative filtering algorithm, we propose a collaborative filtering algorithm based on user demographics and expert opinions. First we compare users’ demographic attributes, which are then compared with expert demographic attributes to calculate the similarities between users and experts. Experimental results verify that the algorithm proposed in this paper can effectively improve the prediction accuracy of collaborative filtering algorithm.

Key words: recommender system;collaborative filtering;demographic correlation;expert opinions