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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 4
1074-1078

Deep recommendation model with context information

Hu Chaoju
Zheng Hao
School of Control & Computer Engineering, North China Electric Power University, Baoding Hebei 071000, China
DOI: 10.19734/j.issn.1001-3695.2020.03.0099

Abstract

At present, in the recommendation task based on document information, the traditional document-based hybrid recom-mendation algorithm still relies on a shallow linear model. When the scoring data becomes huge and complex, its recommendation performance is often not ideal. This paper proposed a deep fusion model(DeepFM), which could fully capture text information and handle complex and sparse scoring data well. DeepFM consisted of two parallel neural networks. One of them used multiple layers of perceptron to extract the row vector information of the rating matrix to obtain the user's potential feature vector. The other one used fusion model of MLP and convolutional neural network(CNN) to extract additional textual information about the item and obtain the item's potential feature vector. Finally, it fused the user feature vector and the item feature vector by constructing a fusion layer to obtain a prediction score. Experimental results show that DeepFM outperforms mainstream recommendation models on MovieLens dataset and Amazon dataset.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.03.0099
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 4
Section: Algorithm Research & Explore
Pages: 1074-1078
Serial Number: 1001-3695(2021)04-020-1074-05

Publish History

[2021-04-05] Printed Article

Cite This Article

胡朝举, 郑浩. 融合上下文信息的深度推荐模型 [J]. 计算机应用研究, 2021, 38 (4): 1074-1078. (Hu Chaoju, Zheng Hao. Deep recommendation model with context information [J]. Application Research of Computers, 2021, 38 (4): 1074-1078. )

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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