A HAsh Learning Framework for search-oriented knowledge graph embedding

Meng Wang, Tongtong Wu, Guilin Qi

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

1 Citation (Scopus)

Abstract

Knowledge graph representation learning, also called knowledge graph embedding, is the task of mapping entities and relations into a low-dimensional, continuous vector space, and, as a result, can support various machine learning models to perform knowledge completion tasks with good performance and robustness. However, most of existing embedding models focus on improving the link prediction accuracy while ignoring the time-efficiency in search-intensive applications over large-scale knowledge graphs. To tackle this problem, in this paper, we encode knowledge graph into Hamming space and introduce a novel HAsh Learning Framework (HALF) for search-oriented knowledge graph embedding. The proposed method can be applied to recent various knowledge graph embedding models for accelerating the computation of searching embeddings by utilizing the bitwise operations (XNOR and Bitcount). Experimental results on benchmark datasets demonstrate the effectiveness of our proposed method, which gets a bonus of speed-up in the searching embeddings while the accuracy and scalability of the original model are basically maintained.

Original languageEnglish
Title of host publicationECAI Digital - 2020
Subtitle of host publication24th European Conference on Artificial Intelligence
EditorsGiuseppe De Giacomo, Alejandro Catala, Bistra Dilkina, Michela Milano, Senen Barro, Alberto Bugarin, Jerome Lang
Place of PublicationAmsterdam Netherlands
PublisherIOS Press
Pages921-928
Number of pages8
ISBN (Electronic)9781643681009
DOIs
Publication statusPublished - 2020
Externally publishedYes
EventEuropean Conference on Artificial Intelligence 2020 - Virtual, Santiago de Compostela, Spain
Duration: 29 Aug 20208 Sept 2020
Conference number: 24th
https://digital.ecai2020.eu (Website)
http://ebooks.iospress.nl/volume/ecai-2020-24th-european-conference-on-artificial-intelligence (Proceedings)

Publication series

NameFrontiers in Artificial Intelligence and Applications
PublisherIOS Press
Volume325
ISSN (Print)0922-6389

Conference

ConferenceEuropean Conference on Artificial Intelligence 2020
Abbreviated titleECAI 2020
Country/TerritorySpain
CitySantiago de Compostela
Period29/08/208/09/20
Other24th European Conference on Artificial Intelligence, ECAI 2020, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020
Internet address

Cite this