Holographic embeddings of knowledge graphs

Holographic embeddings of knowledge graphs

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Learning embeddings of entities and relations is an efficient and versatile method to perform machine learning on relational data such as knowledge graphs. In this work, we propose holographic embeddings (HOLE) to learn compositional vector space representations of entire knowledge graphs. The propo...

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Bibliographic Details
Main Authors: Nickel, Maximilian, Rosasco, Lorenzo, Poggio, Tomaso A
Other Authors: McGovern Institute for Brain Research at MIT. Center for Brains, Minds, and Machines
Format: Article
Published: Association for the Advancement of Artificial Intelligence 2017
Online Access:http://hdl.handle.net/1721.1/112286
https://orcid.org/0000-0001-5006-0827
https://orcid.org/0000-0001-6376-4786
https://orcid.org/0000-0002-3944-0455

Internet

http://hdl.handle.net/1721.1/112286
https://orcid.org/0000-0001-5006-0827
https://orcid.org/0000-0001-6376-4786
https://orcid.org/0000-0002-3944-0455

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