Abstract
This paper describes DBee, a database to support the construction of data-intensive AI applications. DBee provides a unique data model which operates jointly over large-scale knowledge graphs (KGs) and embedding vector spaces (VSs). This model supports queries which exploit the semantic properties of both types of representations (KGs and VSs). Additionally, DBee aims to facilitate the construction of KGs and VSs, by providing a library of generators, which can be used to create, integrate and transform data into KGs and VSs.- Anthology ID:
- D19-5322
- Volume:
- Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13)
- Month:
- November
- Year:
- 2019
- Address:
- Hong Kong
- Editors:
- Dmitry Ustalov, Swapna Somasundaran, Peter Jansen, Goran Glavaš, Martin Riedl, Mihai Surdeanu, Michalis Vazirgiannis
- Venue:
- TextGraphs
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 177–185
- Language:
- URL:
- https://aclanthology.org/D19-5322
- DOI:
- 10.18653/v1/D19-5322
- Cite (ACL):
- Viktor Schlegel and André Freitas. 2019. DBee: A Database for Creating and Managing Knowledge Graphs and Embeddings. In Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13), pages 177–185, Hong Kong. Association for Computational Linguistics.
- Cite (Informal):
- DBee: A Database for Creating and Managing Knowledge Graphs and Embeddings (Schlegel & Freitas, TextGraphs 2019)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/D19-5322.pdf