Confront of the large amount of data generated by the Internet and how to make the inherent *** recommendation system is widely used as a means of making effective use of large data and is followed by the *** filterin...
详细信息
Confront of the large amount of data generated by the Internet and how to make the inherent *** recommendation system is widely used as a means of making effective use of large data and is followed by the *** filtering recommendation algorithm cannot avoid the bottleneck of computing performance problems in the recommendation *** this paper,we propose an improved collaborative filtering recommendation algorithm ***,the rlpso（Reverse-learning and local-learning PSO）algorithm is used to find the optimal solution of particle swarm and output the optimized clustering ***,the rlpsoM algorithm is used to cluster the user ***,the traditional collaborative filtering algorithm is combined with rlpsoM clustering to effectively recommend the target *** experimental results show that the rlpsoMF algorithm has a significant improvement in the recommended accuracy and has a higher stability.
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