PAGE: Answering graph pattern queries via knowledge graph embedding

Sanghyun Hong, Noseong Park, Tanmoy Chakraborty, Hyunjoong Kang, Soonhyun Kwon

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

3 Citations (Scopus)

Abstract

Answering graph pattern queries have been highly dependent on a technique—i.e., subgraph matching, however, this approach is ineffective when knowledge graphs include incorrect or incomplete information. In this paper, we present a method called PAGE that answers graph pattern queries via knowledge graph embedding methods. PAGE computes the energy (or uncertainty) of candidate answers with the learned embeddings and chooses the lower-energy candidates as answers. Our method has the two advantages: (1) PAGE is able to find latent answers hard to be found via subgraph matching and (2) presents a robust metric that enables us to compute the plausibility of an answer. In evaluations with two popular knowledge graphs, Freebase and NELL, PAGE demonstrated the performance increase by up to 28% compared to baseline KGE methods.

Original languageEnglish
Title of host publicationBig Data – BigData 2018 - 7th International Congress, Held as Part of the Services Conference Federation, SCF 2018, Proceedings
EditorsLatifur Khan, Liang-Jie Zhang, Kisung Lee, Francis Y. Chin, C. L. Chen
PublisherSpringer Verlag
Pages87-99
Number of pages13
ISBN (Print)9783319943008
DOIs
Publication statusPublished - 2018 Jan 1
Event7th International Congress on Big Data, BigData 2018 Held as Part of the Services Conference Federation, SCF 2018 - Seattle, United States
Duration: 2018 Jun 252018 Jun 30

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10968 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Congress on Big Data, BigData 2018 Held as Part of the Services Conference Federation, SCF 2018
CountryUnited States
CitySeattle
Period18/6/2518/6/30

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Hong, S., Park, N., Chakraborty, T., Kang, H., & Kwon, S. (2018). PAGE: Answering graph pattern queries via knowledge graph embedding. In L. Khan, L-J. Zhang, K. Lee, F. Y. Chin, & C. L. Chen (Eds.), Big Data – BigData 2018 - 7th International Congress, Held as Part of the Services Conference Federation, SCF 2018, Proceedings (pp. 87-99). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10968 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-94301-5_7