Abstract：In order to improve the recommendation quality of recommendation system when the data are sparse, an improved collaborative filtering algorithm was proposed. Using a data mining algorithm, the sparse rating matrix was filled firstly. Afterwards user-similarities and their confidence factors were calculated using the complete filling matrix. Ultimately, the recommendation forecast was made. Comparative experiments on typical dataset show that the algorithm is able to achieve better results even with extremely sparse data.
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2013, Vol. 33 
