Knowledge Base Embeddings: Semantics and Theoretical Properties
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909282683846656 |
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| author | Bourgaux, Camille Guimarães, Ricardo Koudijs, Raoul Lacerda, Victor Ozaki, Ana |
| author_facet | Bourgaux, Camille Guimarães, Ricardo Koudijs, Raoul Lacerda, Victor Ozaki, Ana |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_04913 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Knowledge Base Embeddings: Semantics and Theoretical Properties Bourgaux, Camille Guimarães, Ricardo Koudijs, Raoul Lacerda, Victor Ozaki, Ana Artificial Intelligence Logic in Computer Science 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. |
| title | Knowledge Base Embeddings: Semantics and Theoretical Properties |
| topic | Artificial Intelligence Logic in Computer Science |
| url | https://arxiv.org/abs/2408.04913 |