Collaborative Filtering Recommendation Optimization Based on User
WEI Ze
ZHOU Dengwen
Abstract：In order to improve accuracy of the traditional collaborative filtering algorithm select user neighbor set, this paper proposes an improved collaborative filtering recommendation algorithm.The algorithm selects the user common rating data to calculate the user's similarity, also considers the consistency of the score data, constructes evaluation matrix, and alleviates the similarity calculation value and actual value deviation by user rating consistent times thanratingitem number as a penalty function is introduced into the similarity calculation.Experimental results show that the improved algorithm proposed in this paper significantly increases the prediction accuracy, so as to improve the quality of recommendation.
Keywords：neighbor setcollaborative filteringconsistent matrixsimilarity
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 613-615,628 )