More Is Better: Sequential Combinations of Knowledge Graph Embedding Approaches

Kemas Wiharja, Jeff Z. Pan, Martin Kollingbaum, Yu Deng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Constructing and maintaining large-scale good quality knowledge graphs present many challenges. Knowledge graph completion has been regarded a promising direction in the knowledge graph community. The majority of current work for knowledge graph completion approaches do not take the schema of a target knowledge graph as input. As a result, the triples generated by these approaches are not necessarily consistent with the schema of the target knowledge graph. This paper proposes to improve the correctness of knowledge graph completion based on Schema Aware Triple Classification (SATC), which enables sequential combinations of knowledge graph embedding approaches. Extensive experiments show that our proposed approaches can significantly improve the correctness of the new triples produced by knowledge graph embedding methods.
Original languageEnglish
Title of host publicationSemantic Technology
Subtitle of host publication8th Joint International Conference, JIST 2018, Awaji, Japan, November 26–28, 2018, Proceedings
EditorsRyutaro Ichise, Freddy Lecue, Takahiro Kawamura, Dongyan Zhao, Stephen Muggleton, Kouji Kozaki
Place of PublicationCham
PublisherSpringer International Publishing
Number of pages17
ISBN (Electronic)978-3-030-04284-4
ISBN (Print)978-3-030-04283-7
Publication statusPublished - 14 Nov 2018
EventThe 8th Joint International Semantic Technology Conference - Awaji City, Japan
Duration: 26 Nov 201828 Nov 2018

Publication series

NameLecture Notes in Computer Science
PublisherSpringer, Cham
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceThe 8th Joint International Semantic Technology Conference
Abbreviated titleJIST 2018
CityAwaji City
Internet address

Keywords / Materials (for Non-textual outputs)

  • Knowledge graph
  • Embedding
  • Schema aware triple classification
  • Knowledge representation and reasoning
  • Approximate reasoning
  • Artificial Intelligence


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