Holographic embeddings of knowledge graphs

Holographic embeddings of knowledge graphs

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 (Contributor), Rosasco, Lorenzo (Contributor), Poggio, Tomaso A (Contributor)
Other Authors: McGovern Institute for Brain Research at MIT. Center for Brains, Minds, and Machines (Contributor), Massachusetts Institute of Technology. Laboratory for Computational and Statistical Learning (Contributor), McGovern Institute for Brain Research at MIT (Contributor)
Format: Article
Language:English
Published: Association for the Advancement of Artificial Intelligence, 2017-11-27T15:33:36Z.
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