{"type":"ScholarlyArticle","title":"Markov Network Based Ontology Matching","authors":[{"name":"Sivan Albagli","slug":"sivan-albagli","given":"Sivan","family":"Albagli","affiliation":""},{"name":"Rachel Ben-Eliyahu-Zohary","slug":"rachel-ben-eliyahu-zohary","given":"Rachel","family":"Ben-Eliyahu-Zohary","affiliation":""},{"name":"Solomon Eyal Shimony","slug":"solomon-eyal-shimony","given":"Solomon Eyal","family":"Shimony","affiliation":""}],"abstract":"iMatch is a probabilistic scheme for ontology matching based on Markov networks, which has several advantages over other probabilistic schemes. First, it uses undirected networks, which better supports the non-causal nature of the dependencies. Second, it handles the high computational complexity involved by approximate reasoning, rather then by ad-hoc pruning. Third, the probabilities that it uses are learned from matched data. Finally, iMatch naturally supports interactive semi-automatic matches. Experiments using the standard benchmark tests that compare our approach with the most promising existing systems show that iMatch is one of the top performers.Sivan Gali Albagli, Solomon Eyal Shimony, Rachel Ben-Eliyahu-Zohary","doi":null,"url":"https://ijcai.org/proceedings/2009/312","pdf":"https://ijcai.org/proceedings/2009/0312.pdf","markdown":"https://ijcai.org/proceedings/2009/312.md","bibtex":"https://ijcai.org/proceedings/2009/bibtex/312","volume":{"slug":"2009","title":"Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2009","url":"https://ijcai.org/proceedings/2009/","year":2009,"location":"Pasadena, California, USA","dates":"","editors":"Hiroaki Kitano","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":312,"pages":{"first":1884,"last":1888},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}