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Knowledge Graph Embedding with Relation Constraint

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Web and Big Data. APWeb-WAIM 2020 International Workshops (APWeb-WAIM 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1373))

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Abstract

Knowledge graph (KG) is structure representations of the real-world facts by triples, and embedding entities and relations of a KG into continuous vector spaces is proven to be effective in many applications. Schema-based KG also has rich prior information about entities and relations, such as entity constraints for relations which define the semantic role of relations. In this paper, we propose TransRC (Translation model with Relation Constraint) model, which use relation constraint as a part of score function to extend the TransE. Experimental results from multiple benchmarks knowledge graph datasets show that the TransRC benefits from relation constraint information, and it is better than other methods on link prediction and triple classification.

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China

    Chunming Yang & Bo Li

  2. School of Science, Southwest University of Science and Technology, Mianyang, 621010, Sichuan, China

    Hui Zhang

  3. Sichuan Branch of China Telecom Co., Ltd., Chengdu, 610015, Sichuan, China

    Xinghao Song

  4. Sichuan Big Data and Intelligent System Engineering Technology Research Center, Mianyang, 621010, Sichuan, China

    Chunming Yang

Authors
  1. Chunming Yang
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  2. Xinghao Song
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  3. Hui Zhang
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  4. Bo Li
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Corresponding author

Correspondence to Chunming Yang .

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Editors and Affiliations

  1. Northwestern Polytechnical University, Xi’an, China

    Qun Chen

  2. Deakin University, Geelong, VIC, Australia

    Jianxin Li

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Yang, C., Song, X., Zhang, H., Li, B. (2021). Knowledge Graph Embedding with Relation Constraint. In: Chen, Q., Li, J. (eds) Web and Big Data. APWeb-WAIM 2020 International Workshops. APWeb-WAIM 2020. Communications in Computer and Information Science, vol 1373. Springer, Singapore. https://doi.org/10.1007/978-981-16-0479-9_4

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  • DOI: https://doi.org/10.1007/978-981-16-0479-9_4

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