KR2024Proceedings of the 21st International Conference on Principles of Knowledge Representation and ReasoningProceedings of the 21st International Conference on Principles of Knowledge Representation and Reasoning

Hanoi, Vietnam. November 2-8, 2024.

Edited by

ISSN: 2334-1033
ISBN: 978-1-956792-05-8

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Published by

Copyright © 2024 International Joint Conferences on Artificial Intelligence Organization

Knowledge Base Embeddings: Semantics and Theoretical Properties

  1. Camille Bourgaux(DI ENS, ENS, CNRS, PSL University & Inria)
  2. Ricardo Guimarães(University of Bergen)
  3. Raoul Koudijs(University of Bergen)
  4. Victor Lacerda(University of Bergen)
  5. Ana Ozaki(University of Bergen, University of Oslo)

Keywords

  1. KR and Embeddings-General

Abstract

Research on knowledge graph embeddings has recently evolved into knowledge base embeddings, where the goal is not only to map facts into vector spaces but also constrain the models so that they take into account the relevant conceptual knowledge available. This paper examines recent methods that have been proposed to embed knowledge bases in description logic into vector spaces through the lens of their geometric-based semantics. We identify several relevant theoretical properties, which we draw from the literature and sometimes generalize or unify. We then investigate how concrete embedding methods fit in this theoretical framework.