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Author:

Xue, Yiqi (Xue, Yiqi.) | Zhang, Weidong (Zhang, Weidong.) | Wu, Junyi (Wu, Junyi.) | Xu, Xiaobin (Xu, Xiaobin.)

Indexed by:

CPCI-S

Abstract:

With the development of the Internet, the information in the network is growing explosively, and the information surplus brings a great burden to people in screening and selecting information. Collaborative filtering recommendation can effectively realize information filtering. There are many applications in various scenarios. Currently, collaborative filtering recommendation methods can be roughly divided into two types: explicit feedback based recommendation and implicit feedback based recommendation. In recent years, algorithms for implicit feedback recommendation have developed rapidly, and many excellent algorithms have emerged, the performance of recommendation algorithm based on explicit feedback still needs to be improved. This paper analyzes and models human cognitive behavior, and proposes a subjective and objective evaluation transformation model. Based on this model, a recommendation algorithm based on explicit feedback is proposed. Simulation results show that the algorithm has good performance in recommendation accuracy.

Keyword:

subjective and objective evaluation conversion component formatting explicit feedback intelligent cognition collaborative filtering recommendation

Author Community:

  • [ 1 ] [Xue, Yiqi]Beijing Univ Technol, Adv Innovat Ctr Future Internet Technol, Beijing, Peoples R China
  • [ 2 ] [Xu, Xiaobin]Beijing Univ Technol, Adv Innovat Ctr Future Internet Technol, Beijing, Peoples R China
  • [ 3 ] [Zhang, Weidong]Space Integrated Ground Informat Network Co Ltd, China Elect Technol Corp, Beijing, Peoples R China
  • [ 4 ] [Wu, Junyi]Space Integrated Ground Informat Network Co Ltd, China Elect Technol Corp, Beijing, Peoples R China

Reprint Author's Address:

  • [Xue, Yiqi]Beijing Univ Technol, Adv Innovat Ctr Future Internet Technol, Beijing, Peoples R China

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Source :

PROCEEDINGS OF 2020 IEEE 11TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS 2020)

ISSN: 2327-0594

Year: 2020

Page: 167-170

Language: English

Cited Count:

WoS CC Cited Count: 2

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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