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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 10
3030-3034

Depth recommendation based on FG_DRFwFm model

Wang Shanwen
Ou Ou
Zhang Weijin
Ou Yangfei
College of Information Science & Technology(College of Internet Security), Chengdu University of Technology, Chengdu 610051, China
DOI: 10.19734/j.issn.1001-3695.2021.02.0048

Abstract

In recent years, as deep learning has achieved good results in many fields, deep learning has also begun to be applied to recommendation systems, such as NFM models and DeepFM models that use deep learning technology to capture high-level feature interactions. However, considering the changes in the external environment and internal perception, the user's interest should also change dynamically over time, and the combination based on the original features may not necessarily learn effective feature interaction. This paper attempted to build a new model FG_DRFwFm, which could learn the interaction of low-level and high-level features of multiple feature domains and dealt with long-term changes in user interest. It constructed the training features by constructing new features based on the original features and splicing them together, which could better learn effective feature interaction. Finally, the proposed model compared the recommendation effect with multiple advanced CTR algorithms on the MovieLens data set. The experimental results show that the proposed model achieves better results.

Foundation Support

国家重点研发计划资助项目(2018YFF01013304)
贵州地质灾害预警平台调查评价系统(80303-AHG069)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.02.0048
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 10
Section: Algorithm Research & Explore
Pages: 3030-3034
Serial Number: 1001-3695(2021)10-025-3030-05

Publish History

[2021-10-05] Printed Article

Cite This Article

王杉文, 欧鸥, 张伟劲, 等. 基于FG_DRFwFm模型的深度推荐 [J]. 计算机应用研究, 2021, 38 (10): 3030-3034. (Wang Shanwen, Ou Ou, Zhang Weijin, et al. Depth recommendation based on FG_DRFwFm model [J]. Application Research of Computers, 2021, 38 (10): 3030-3034. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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