{"type":"ScholarlyArticle","title":"Evolutionary Learning of Existential Rules","authors":[{"name":"Lianlong Wu","slug":"lianlong-wu","given":"Lianlong","family":"Wu","affiliation":"Department of Computer Science , University of Oxford , United Kingdom"}],"abstract":"Declarative rules such as Prolog and Datalog are common formalisms to express expert knowledge and are used in a number of systems. Since developing such rules is time-consuming and requires scarce expert knowledge, it is essential to develop algorithms for learning such rules. We address the problem of learning existential rules, a richer class of rules which found applications in many use-cases such as Semantic Web and Web Data Extraction. In particular, we concentrate on developing evolutionary learning algorithms for rule learning.","doi":"10.24963/ijcai.2019/928","url":"https://ijcai.org/proceedings/2019/928","pdf":"https://ijcai.org/proceedings/2019/0928.pdf","markdown":"https://ijcai.org/proceedings/2019/928.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/928","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Doctoral Consortium","track":"Doctoral Consortium","number":928,"pages":{"first":6478,"last":6479},"keywords":["Knowledge Representation and Reasoning: Logics for Knowledge Representation","Knowledge Representation and Reasoning: Knowledge Representation Languages","Machine Learning: Knowledge-based Learning","Machine Learning Applications: Applications of Supervised Learning"],"videos":[],"references":[{"position":1,"raw":"[Bellomarini et al., 2018] Luigi Bellomarini, Emanuel Sallinger, and Georg Gottlob. The Vadalog System : Datalog-based Reasoning for Knowledge Graphs. In VLDB, 2018.","title":"The Vadalog System : Datalog-based Reasoning for Knowledge Graphs","authors":"Bellomarini","year":"2018","venue":"VLDB","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Cal et al., 2010] Andrea Cal, Georg Gottlob, Thomas Lukasiewicz, Bruno Marnette, and Andreas Pieris. Dat- alog + / -: A Family of Logical Knowledge Representa- tion and Query Languages for New Applications. In LICS, 2010.","title":"Datalog + / -: A Family of Logical Knowledge Representation and Query Languages for New Applications","authors":"Andrea Cal, Georg Gottlob, Thomas Lukasiewicz, Bruno Marnette, Andreas Pieris","year":"2010","venue":"LICS","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Dai and Zhou, 2019] Wang Zhou Dai and Zhi Hua Zhou. A Survey on Inductive Logic Programming. Journal of com- puter Research and Development, 56(1):138-154, 2019.","title":"A Survey on Inductive Logic Programming","authors":"Wang Zhou, Dai, Zhi Hua Zhou","year":"2019","venue":"Journal of computer Research and Development","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Fürnkranz et al., 2012] Johannes Fürnkranz, Dragan Gam- berger, and Nada Lavrač. Foundations of Rule Learning. Springer-Verlag Berlin Heidelberg, 2012.","title":"Johannes Fürnkranz, Dragan Gamberger, and Nada Lavrač. Foundations of Rule Learning","authors":"Fürnkranz","year":"2012","venue":null,"doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Nienhuys-Cheng and de Wolf, 1997] Shan-Hwei Nienhuys-Cheng and Ronald de Wolf. Foundations of inductive logic programming. Springer, 1997.","title":"Foundations of inductive logic programming","authors":"Nienhuys-Cheng, De Wolf, ; Shan-Hwei Nienhuys-Cheng, Ronald De, Wolf","year":"1997","venue":null,"doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}