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Swift Logic for Big Data and Knowledge Graphs

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https://www.ijcai.org/proceedings/2017/0001.pdf
Original languageEnglish
Title of host publicationProceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI-17)
PublisherIJCAI Inc
Pages2-10
Number of pages9
ISBN (Electronic) 978-0-9992411-0-3
DOIs
Publication statusPublished - 25 Aug 2017
Event26th International Joint Conference on Artificial Intelligence - Melbourne, Australia
Duration: 19 Aug 201725 Aug 2017
https://ijcai-17.org/index.html
https://ijcai-17.org/
https://ijcai-17.org/

Conference

Conference26th International Joint Conference on Artificial Intelligence
Abbreviated titleIJCAI 2017
CountryAustralia
CityMelbourne
Period19/08/1725/08/17
Internet address

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.

Event

26th International Joint Conference on Artificial Intelligence

19/08/1725/08/17

Melbourne, Australia

Event: Conference

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