DOME Results for OAEI 2019

URL:	http://ceur-ws.org/Vol-2536/oaei19_paper6.pdf
Additional URL:	http://ceur-ws.org/Vol-2536/
Document Type:	Conference or workshop publication
Year of publication:	2019
Book title:	OM 2019 : Proceedings of the 14th International Workshop on Ontology Matching co-located with the 18th International Semantic Web Conference (ISWC 2019) Auckland, New Zealand, October 26, 2019
The title of a journal, publication series:	CEUR Workshop Proceedings
Volume:	2536
Page range:	123-130
Conference title:	OM 2019
Location of the conference venue:	Auckland, NZ
Date of the conference:	26.10.2019
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
Keywords (English):	Ontology Matching , Knowledge Graph , Doc2Vec
Abstract:	DOME (Deep Ontology MatchEr) is a scalable matcher for instance and schema matching which relies on large texts describing the ontological concepts. The doc2vec approach is used to generate a vector representation of the concepts based on the textual information contained in literals. The cosine distance between two concepts in the embedding space is used as a confidence value. In comparison to the previous version of DOME it uses an instance based class matching approach. Due to its high scalability, it can also produce results in the largebio track of OAEI and can be applied to very large knowledge graphs. The results look promising if huge texts are available, but there is still a lot of room for improvement.