ML Anthology

Swift Logic for Big Data and Knowledge Graphs

Luigi Bellomarini, Georg Gottlob, Andreas Pieris, Emanuel Sallinger
IJCAI 2017 pp. 2-10
doi:10.24963/IJCAI.2017/1 /ijcai/2017/bellomarini2017ijcai-swift/

Abstract

Many modern companies wish to maintain knowledge in the form of a corporate knowledge graph and to use and manage this knowledge via a knowledge graph management system (KGMS). We formulate various requirements for a fully fledged KGMS. In particular, such a system must be capable of performing complex reasoning tasks but, at the same time, achieve efficient and scalable reasoning over Big Data with an acceptable computational complexity. Moreover, a KGMS needs interfaces to corporate databases, the web, and machine-learning and analytics packages. We present KRR formalisms and a system achieving these goals.

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Cite

Text

Bellomarini et al. "Swift Logic for Big Data and Knowledge Graphs." International Joint Conference on Artificial Intelligence, 2017. doi:10.24963/IJCAI.2017/1

Markdown

[Bellomarini et al. "Swift Logic for Big Data and Knowledge Graphs." International Joint Conference on Artificial Intelligence, 2017.](https://mlanthology.org/ijcai/2017/bellomarini2017ijcai-swift/) doi:10.24963/IJCAI.2017/1

BibTeX

@inproceedings{bellomarini2017ijcai-swift,
  title     = {{Swift Logic for Big Data and Knowledge Graphs}},
  author    = {Bellomarini, Luigi and Gottlob, Georg and Pieris, Andreas and Sallinger, Emanuel},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2017},
  pages     = {2-10},
  doi       = {10.24963/IJCAI.2017/1},
  url       = {https://mlanthology.org/ijcai/2017/bellomarini2017ijcai-swift/}
}