Computer Science

Computer Science ›› 2018, Vol. 45 ›› Issue (6A): 398-401.

• Big Date & Date Mining • Previous Articles     Next Articles

Collaboration Filtering Recommendation Algorithm Based on Ratings Difference
and Interest Similarity

WEI Hui-juan, DAI Mu-hong   

  1. College of Information Science and Engineering,Hunan University,Changsha 410082,China
  • Online:2018-06-20 Published:2018-08-03

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Abstract: In order to improve the quality of recommendation system and solve the existing similarity calculation inaccuracy problem of traditional collaborative filtering algorithm,this paper put forward a method to calculate user similarity.Based on the user common ratings,this method firstly calculates the information entropy of rating differentials according to rating differentials and time features.Then it evaluates the similarity of the user by utilizing the information entropy of rating differentials and the rated item attributes.Finally,the nearest neighbors would be calculated according to the user similarity,which helps predict the rating of the target item.The experimental results show that the proposed algorithm makes the target user find the nearest neighbors more accurately and improves the recommendation accuracy effectively.

Key words: Collaborative filtering, Common ratings, Item attributes, Similarity measure

CLC Number: 

  • TP311.5
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