Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 12
3587-3591,3597

Recommendation systems based on attention mechanism and meta-paths of heterogeneous information network

Jiang Zhenghe
Chen Xuegang
Institute of Mathematical & Physical Sciences, North China Electric Power University, Beijing 102206, China
DOI: 10.19734/j.issn.1001-3695.2022.05.0248

Abstract

Because heterogeneous information network(HIN) contains rich network structure and semantic information, recommendation systems often use HIN for recommendation. However, the current researches of recommender systems is mainly based on indirect information provided by meta-paths for recommendation, but these researches don't make full use of direct interactive information. To make full use of this information, this paper proposed a ternary interaction model(AMMRec) that incorporated attention mechanisms and heterogeneous information network meta-paths. This method firstly used the implicit feedback matrix to construct user similarity matrix and item similarity matrix and used the representation learning method of the HIN to obtain the corresponding feature vector embeddings in HIN. Then it used the the attention mechanism to modify the embeddings and designed attention neural network to fuse representation vectors of different meta-paths. Finally it concatenated user embeddings and meta-path embeddings and item embeddings, and generated recommendation results through fully connected neural network. The experimental results on real datasets show that AMMRec improves the recommendation accuracy by up to 9.5%. In addition, AMMRec has good interpretability for the recommendation results.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.05.0248
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 12
Section: Algorithm Research & Explore
Pages: 3587-3591,3597
Serial Number: 1001-3695(2022)12-009-3587-05

Publish History

[2022-08-04] Accepted Paper
[2022-12-05] Printed Article

Cite This Article

姜征和, 陈学刚. 基于注意力机制和异质信息网络元路径的推荐系统 [J]. 计算机应用研究, 2022, 39 (12): 3587-3591,3597. (Jiang Zhenghe, Chen Xuegang. Recommendation systems based on attention mechanism and meta-paths of heterogeneous information network [J]. Application Research of Computers, 2022, 39 (12): 3587-3591,3597. )

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  • 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.

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