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作者:

He, Siyuan (He, Siyuan.) | Li, Tao (Li, Tao.) | Duan, Yuxin (Duan, Yuxin.) | Yang, Zhenning (Yang, Zhenning.) | Li, Feixiang (Li, Feixiang.)

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摘要:

the recommendation system is one of the core tasks of data mining. It divided into the recommendation system for explicit feedback and the recommendation system for implicit feedback. In recent years, many researchers have combined deep learning with recommendation system of explicit feedback and achieved excellent results. But it is very rare for implicit feedback. In this paper, we apply deep learning to the recommendation system for implicit feedback, and propose a new model that is combined with Neural Collaborative Filtering and Variable automatic-encoder. We use the MovieLens dataset to evaluate our proposed model. Experimental results show that the proposed model effectively improves the accuracy and quality of the recommended results, the Precision is 0.715 and the NDCG is 0.436 without manual parameters. © 2019 IEEE.

关键词:

Collaborative filtering Data mining Deep learning Learning systems Recommender systems Signal encoding

作者机构:

  • [ 1 ] [He, Siyuan]Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, China
  • [ 2 ] [Li, Tao]School of Software Engineering, University of Science and Technology of China, China
  • [ 3 ] [Duan, Yuxin]Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, China
  • [ 4 ] [Yang, Zhenning]School of Software Engineering, Beijing University of Technology, China
  • [ 5 ] [Li, Feixiang]Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, China

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年份: 2019

页码: 512-516

语种: 英文

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SCOPUS被引频次: 2

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