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Algorithm Research & Explore
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1759-1764

Research on knowledge graph representation learning combining entity concept description and image features

Jiao Linjinga
Yan Weia,b
a. School of Information, b. School of Innovation & Entrepreneurship, Liaoning University, Shenyang 110036, China

Abstract

The representation learning of knowledge graph aims to map entities and relationships to a continuous low-dimensional space. The traditional learning method is to learn knowledge representation from structured triples, ignore the rich multi-source information related to entities other than triples. Aiming at this problem, this paper proposed a knowledge graph representation learning model DIRL, which combined entity concept description and image features with fact triples. Firstly, this method used the BERT model to perform the semantic representation of the entity concept description. Secondly, it used the CNN encoder to extract the overall features of the image, and then represented the image features by the attention-based method. Finally, the method combined the concept description-based representation and the image features-based representation with translation model TransR for knowledge graph representation learning. The experimental results demonstrate that the DIRL model outperforms the existing methods, which improves the effectiveness of the representation of multi-source information knowledge graph.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.06.0164
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 6
Section: Algorithm Research & Explore
Pages: 1759-1764
Serial Number: 1001-3695(2021)06-029-1759-06

Publish History

[2021-06-05] Printed Article

Cite This Article

缴霖境, 闫威. 融合实体概念描述与图像特征的知识图谱表示学习研究 [J]. 计算机应用研究, 2021, 38 (6): 1759-1764. (Jiao Linjing, Yan Wei. Research on knowledge graph representation learning combining entity concept description and image features [J]. Application Research of Computers, 2021, 38 (6): 1759-1764. )

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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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