{"type":"ScholarlyArticle","title":"Swift Logic for Big Data and Knowledge Graphs","authors":[{"name":"Luigi Bellomarini","slug":"luigi-bellomarini","given":"Luigi","family":"Bellomarini","affiliation":"Department of Computer Science , University of Oxford , UK"},{"name":"Georg Gottlob","slug":"georg-gottlob","given":"Georg","family":"Gottlob","affiliation":"Department of Computer Science , University of Oxford , UK; Institute of Information Systems , TU Wien , Austria"},{"name":"Andreas Pieris","slug":"andreas-pieris","given":"Andreas","family":"Pieris","affiliation":"School of Informatics , University of Edinburgh , UK"},{"name":"Emanuel Sallinger","slug":"emanuel-sallinger","given":"Emanuel","family":"Sallinger","affiliation":"Department of Computer Science , University of Oxford , UK"}],"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  \r\ncapable 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. \r\nWe present KRR formalisms and a system achieving these goals.","doi":"10.24963/ijcai.2017/1","url":"https://ijcai.org/proceedings/2017/1","pdf":"https://ijcai.org/proceedings/2017/0001.pdf","markdown":"https://ijcai.org/proceedings/2017/1.md","bibtex":"https://ijcai.org/proceedings/2017/bibtex/1","volume":{"slug":"2017","title":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2017","url":"https://ijcai.org/proceedings/2017/","year":2017,"location":"Melbourne, Australia","dates":"19-25 August 2017","editors":"Carles Sierra","isbn":"978-0-9992411-0-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2017"},"section":"Invited Speakers","track":"Invited Speakers","number":1,"pages":{"first":2,"last":10},"keywords":["Knowledge Representation, Reasoning, and Logic: Computational Complexity of Reasoning","Knowledge Representation, Reasoning, and Logic: Logics for Knowledge Representation","Knowledge Representation, Reasoning, and Logic: Description Logics and Ontologies","Multidisciplinary Topics and Applications: Database Systems"],"videos":[],"references":[{"position":1,"raw":"[Afrati et al., 2003] Foto N. 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