Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 6
1742-1748

Recommendation model combining enhanced collaborative information and knowledge graph information

Tao Jia
Huang Xianying
Gao Yulan
School of Computer Science & Engineering, Chongqing University of Technology, Chongqing 400054, China
DOI: 10.19734/j.issn.1001-3695.2021.10.0606

Abstract

The recommender system uses knowledge graph can solve the problems of data sparsity and cold start, but it often ignores the importance of high-order collaborative information and different collaborative information to explore users' potential preferences. Therefore, this paper proposed a recommendation model combining enhanced collaborative information and know-ledge graph information(CIKG). This model first used the historical interactive data of users and items to obtain first-order collaboration information and high-order collaboration information. At the same time, it used the attention mechanism to capture important information and obtain enhanced collaboration information to supplement the feature representation of users and items. Secondly, this model matched interacted items with the entities in the knowledge graph and performed the propagation in the knowledge graph. It could obtain knowledge graph information and used the information to obtain the user's preferences and enhance the interpretability of the model. Finally, the aggregator combined the enhanced collaboration information and knowledge graph information to obtain the final representation of users and items, so as to make predictions. The experimental results on Last-fm and Book-crossing datasets show that CIKG has a great improvement over other comparative models.

Foundation Support

重庆市社会科学规划项目(2021NDYB101)
国家自然科学基金资助项目(62141201)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.10.0606
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 6
Section: Algorithm Research & Explore
Pages: 1742-1748
Serial Number: 1001-3695(2022)06-024-1742-07

Publish History

[2022-01-14] Accepted Paper
[2022-06-05] Printed Article

Cite This Article

陶佳, 黄贤英, 高钰澜. 融合增强协同信息和知识图谱信息的推荐模型 [J]. 计算机应用研究, 2022, 39 (6): 1742-1748. (Tao Jia, Huang Xianying, Gao Yulan. Recommendation model combining enhanced collaborative information and knowledge graph information [J]. Application Research of Computers, 2022, 39 (6): 1742-1748. )

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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