تقرير
Knowledge Base Embeddings: Semantics and Theoretical Properties
| العنوان: | Knowledge Base Embeddings: Semantics and Theoretical Properties |
|---|---|
| المؤلفون: | Bourgaux, Camille, Guimarães, Ricardo, Koudijs, Raoul, Lacerda, Victor, Ozaki, Ana |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Artificial Intelligence, Computer Science - Logic in Computer Science |
| الوصف: | 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. Comment: This is an extended version of a paper appearing at the 21st International Conference on Principles of Knowledge Representation and Reasoning (KR 2024). 17 pages |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2408.04913 |
| رقم الأكسشن: | edsarx.2408.04913 |
| قاعدة البيانات: | arXiv |
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