Computer Science ›› 2017, Vol. 44 ›› Issue (2): 103-106.doi: 10.11896/j.issn.1002-137X.2017.02.014

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Collaborative Filtering Recommendation Algorithm Based on User Characteristics and Expert Opinions

GAO Fa-zhan, HUANG Meng-xing and ZHANG Ting-ting   

  • Online:2018-11-13 Published:2018-11-13

Abstract: Collaborative filtering recommendation algorithm is one of the most widely used algorithms in recommender system.After analyzing the low precision problem caused by sparse data in conventional collaboration filtering algorithms,this paper proposed an collaboration filtering algorithm which integrates user characteristics and expert opi-nions.The algorithm analyzes user characteristics,compares the similarity between users and experts,and then calculates the similarity matrix.Our algorithm reduces the sparsity of dataset and improves the accuracy of prediction.Our experimental results based on the MovieLens dataset show that,by using our algorithm,performance on the cold start problem and relevant accuracy of recommendation has greatly improved.

Key words: Expert opinions,User characteristics,Collaborative filtering

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