Computer Science ›› 2018, Vol. 45 ›› Issue (5): 190-195.doi: 10.11896/j.issn.1002-137X.2018.05.032

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Collaborative Filtering Recommendation Algorithm Based on Difference and Correlation of Users’ Ratings

WANG Jing-song, CAI Zhao-hui, LI Yong-kai and LIU Shu-bo   

  • Online:2018-05-15 Published:2018-07-25

Abstract: The traditional similarity measurement in collaborative filtering mainly pays attention to the similarity between users’ ratings,lacking the consideration of difference of users’ ratings.This paper divided the relationship of users’ ratings into differential part and correlated part,and proposed a similarity measurement based on the difference and the correlation of users’ ratings on the non-sparse dataset.In order to solve the problem that the algorithm’s recommendation is not accurate in spare dataset,this paper improved this algorithm by prefilling the vacancy of rating matrix.Experiment results show that this algorithm can significantly improve the accuracy of recommendation after prefil-ling the rating matrix.

Key words: Collaborative filtering recommendation,Difference,Correlation,Prefilling

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