Computer Science ›› 2016, Vol. 43 ›› Issue (8): 165-170.doi: 10.11896/j.issn.1002-137X.2016.08.034

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Personalized Recommendation Algorithm Based on Similar Cloud and Measurement by Multifactor

SUN Guang-ming, WANG Shuo and LI Wei-sheng   

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

Abstract: Aiming at the problems of sparse data,occasionality that caused by attribute’s strict matching and measuring with single rating in similarity computation,this paper presented a personalized recommendation algorithm based on similar cloud and measurement by multifactor.The algorithm defines a marking cloud classified by item to fill sparse matrix,and puts forward a feature vector of item’s interest degree consisting of item category,mean score,frequency of rating and accessing,which contributes to calculating the item’s similarity with cloud model.On this basis,this algorithm predicts item’s score in different categories according to the nearest neighbors,and gets the item’s finally score based on a new weighted average computing method.Experimental results show that the algorithm produces more accurate neighbors and better recommendation quality.

Key words: Similar cloud,Measurement by multifactor,Similarity degree,Weigthed average,Personalized algorithm

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