Computer Science ›› 2016, Vol. 43 ›› Issue (Z11): 451-454.doi: 10.11896/j.issn.1002-137X.2016.11A.101

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Time-weighted Hybrid Recommender Algorithm

ZOU Ling-jun, CHEN Ling and LI Juan   

  • Online:2018-12-01 Published:2018-12-01

Abstract: This paper proposed a novel Time-weighted Hybrid Recommender algorithm.The algorithm was divided into an online component and an offline component.The offline component derives the similar group of the target recommendation user according to the information such as evaluation information and constructed object profile model while the online component constructed user profile model according to both target user and the neighbors’ behavior.Because user preferences are drifting over time,the method uses attenuation coefficient in user profile model to improve the recommendation quality.The method uses sliding windows which is divided into several equal segments to produce personalized recommendation in each segment and update user profile model as well as the neighbors in a certain interval.The experimental results show that the algorithm can reflect user preferences over time,and has better effectiveness and achieves a more satisfactory effort.

Key words: Personalized recommendation,Time-weighted,Hybrid recommendation,Logistic function

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