DOME results for OAEI 2018

URL:	http://ceur-ws.org/Vol-2288/oaei18_paper5.pdf
Additional URL:	http://ceur-ws.org/Vol-2288
Document Type:	Conference or workshop publication
Year of publication:	2018
Book title:	OM 2018 : Proceedings of the 13th International Workshop on Ontology Matching co-located with the 17th International Semantic Web Conference (ISWC 2018) Monterey, CA, USA, October 8, 2018
The title of a journal, publication series:	CEUR Workshop Proceedings
Volume:	2288
Page range:	144-151
Conference title:	OM 2018
Location of the conference venue:	Monterey, CA
Date of the conference:	08.10.2018
Publisher:	Shvaiko, Pavel
Place of publication:	Aachen, Germany
Publishing house:	RWTH Aachen
ISSN:	1613-0073
Publication language:	English
Institution:	School of Business Informatics and Mathematics > Data Science (Paulheim 2018-)
Subject:	004 Computer science, internet
Abstract:	DOME (Deep Ontology MatchEr) is a scalable matcher which relies on large texts describing the ontological concepts. Using the doc2vec approach, these texts are used to train a fixed-length vector representation of the concepts. Mappings are generated if two concepts are close to each other in the resulting vector space. If no large texts are available, DOME falls back to a string based matching technique. Due to its high scalability, it can also produce results in the largebio track of OAEI and can be applied to very large ontologies. The results look promising if huge texts are available, but there is still a lot of room for improvement.