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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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CPCI-S

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.

关键词:

Variable automatic-encoder Implicit Feedback Deep learning Recommended System Neural Collaborative Filtering

作者机构:

  • [ 1 ] [He, Siyuan]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing, Peoples R China
  • [ 2 ] [Duan, Yuxin]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing, Peoples R China
  • [ 3 ] [Li, Feixiang]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing, Peoples R China
  • [ 4 ] [Li, Tao]Univ Sci & Technol China, Sch Software Engn, Hefei, Anhui, Peoples R China
  • [ 5 ] [Yang, Zhenning]Beijing Univ Technol, Sch Software Engn, Beijing, Peoples R China

通讯作者信息:

  • [He, Siyuan]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing, Peoples R China

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来源 :

PROCEEDINGS OF 2019 IEEE 8TH JOINT INTERNATIONAL INFORMATION TECHNOLOGY AND ARTIFICIAL INTELLIGENCE CONFERENCE (ITAIC 2019)

年份: 2019

页码: 512-516

语种: 英文

被引次数:

WoS核心集被引频次: 2

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