Rule-Guided Compositional Representation Learning on Knowledge Graphs with Hierarchical Types

Yanying Mao and Honghui Chen
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Yanying Mao: Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, China
Honghui Chen: Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, China

Mathematics, 2021, vol. 9, issue 16, 1-11

Abstract: The representation learning of the knowledge graph projects the entities and relationships in the triples into a low-dimensional continuous vector space. Early representation learning mostly focused on the information contained in the triplet itself but ignored other useful information. Since entities have different types of representations in different scenarios, the rich information in the types of entity levels is helpful for obtaining a more complete knowledge representation. In this paper, a new knowledge representation frame (TRKRL) combining rule path information and entity hierarchical type information is proposed to exploit interpretability of logical rules and the advantages of entity hierarchical types. Specifically, for entity hierarchical type information, we consider that entities have multiple representations of different types, as well as treat it as the projection matrix of entities, using the type encoder to model entity hierarchical types. For rule path information, we mine Horn rules from the knowledge graph to guide the synthesis of relations in paths. Experimental results show that TRKRL outperforms baselines on the knowledge graph completion task, which indicates that our model is capable of using entity hierarchical type information, relation paths information, and logic rules information for representation learning.

Keywords: knowledge graph; representation learning; hierarchical types; logic rules (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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