TY  - EJOU
AU  - Jiang, Weijin  
AU  - Chen, Jiahui  
AU  - Jiang, Yirong  
AU  - Xu, Yuhui  
AU  - Wang, Yang  
AU  - Tan, Lina  
AU  - Liang, Guo  

TI  - A New Time-Aware Collaborative Filtering Intelligent Recommendation System
T2  - Computers, Materials \& Continua

PY  - 2019
VL  - 61
IS  - 2
SN  - 1546-2226

AB  - Aiming at the problem that the traditional collaborative filtering recommendation algorithm does not fully consider the influence of correlation between projects on recommendation accuracy, this paper introduces project attribute fuzzy matrix, measures the project relevance through fuzzy clustering method, and classifies all project attributes. Then, the weight of the project relevance is introduced in the user similarity calculation, so that the nearest neighbor search is more accurate. In the prediction scoring section, considering the change of user interest with time, it is proposed to use the time weighting function to improve the influence of the time effect of the evaluation, so that the newer evaluation information in the system has a relatively large weight. The experimental results show that the improved algorithm improves the recommendation accuracy and improves the recommendation quality.
KW  - Fuzzy clustering
KW  -  time weight
KW  -  attenuation function
KW  -  Collaborative filtering method
KW  -  recommendation algorithm

DO  - 10.32604/cmc.2019.05932