Computer Science ›› 2017, Vol. 44 ›› Issue (9): 243-249.doi: 10.11896/j.issn.1002-137X.2017.09.046

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Collaborative Filtering Algorithm Incorporating Time Factor and User Preference Properties

ZENG An, GAO Cheng-si and XU Xiao-qiang   

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

Abstract: To alleviate the impact of data sparsity and overcome the limits of traditional collaborative filtering algorithm,a novel collaborative filtering algorithm(CF-TP) by incorporating time factor and user preference properties was proposed.A user-item rating matrix is firstly converted to a user-item preference matrix by introducing a preference model,and this helps to reduce the impact of different users’ rating habits.Then the asymmetric impact between users is taken into consideration when computing the predicted scores.What’s more important,to further improve the accuracy of top-N recommendation,the time weight function considering uses’ dynamic interest changed with time is designed.The experiment results on HetRec2011 and MovieLens1M data set suggest that the proposed algorithm is superior to other advanced approaches in precision,recall and F1.

Key words: Recommender system,Collaborative filtering,Time factor,User preference,Asymmetric

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