@inproceedings{schlegel-freitas-2019-dbee,
title = "{DB}ee: A Database for Creating and Managing Knowledge Graphs and Embeddings",
author = "Schlegel, Viktor and
Freitas, Andr{\'e}",
editor = "Ustalov, Dmitry and
Somasundaran, Swapna and
Jansen, Peter and
Glava{\v{s}}, Goran and
Riedl, Martin and
Surdeanu, Mihai and
Vazirgiannis, Michalis",
booktitle = "Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13)",
month = nov,
year = "2019",
address = "Hong Kong",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-5322",
doi = "10.18653/v1/D19-5322",
pages = "177--185",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T DBee: A Database for Creating and Managing Knowledge Graphs and Embeddings
%A Schlegel, Viktor
%A Freitas, André
%Y Ustalov, Dmitry
%Y Somasundaran, Swapna
%Y Jansen, Peter
%Y Glavaš, Goran
%Y Riedl, Martin
%Y Surdeanu, Mihai
%Y Vazirgiannis, Michalis
%S Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13)
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong
%F schlegel-freitas-2019-dbee
%X 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.
%R 10.18653/v1/D19-5322
%U https://aclanthology.org/D19-5322
%U https://doi.org/10.18653/v1/D19-5322
%P 177-185
Markdown (Informal)
[DBee: A Database for Creating and Managing Knowledge Graphs and Embeddings](https://aclanthology.org/D19-5322) (Schlegel & Freitas, TextGraphs 2019)
ACL