Wiktionary matcher results for OAEI 2020

Portisch, Jan ; Paulheim, Heiko

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URL: https://madoc.bib.uni-mannheim.de/58766
Additional URL: http://ceur-ws.org/Vol-2788/oaei20_paper14.pdf
URN: urn:nbn:de:bsz:180-madoc-587663
Document Type: Conference or workshop publication
Year of publication: 2020
Book title: OM 2020 : Proceedings of the 15th International Workshop on Ontology Matching co-located with the 19th International Semantic Web Conference (ISWC 2020) Virtual conference (originally planned to be in Athens, Greece), November 2, 2020
The title of a journal, publication series: CEUR Workshop Proceedings
Volume: 2788
Page range: 225-232
Conference title: OM 2020
Location of the conference venue: Online
Date of the conference: 02.11.2020
Publisher: Shvaiko, Pavel ; Euzenat, Jérôme ; Jiménez-Ruiz, Ernesto ; Hassanzadeh, Oktie ; Trojahn, Cássia
Place of publication: Aachen, Germany
Publishing house: RWTH Aachen
ISSN: 1613-0073
Publication language: English
Institution: School of Business Informatics and Mathematics > Web Data Mining (Paulheim 2018-)
Pre-existing license: Creative Commons Attribution 4.0 International (CC BY 4.0)
Subject: 004 Computer science, internet
Individual keywords (German): Datenintegration , Semantische Integration
Keywords (English): ontology matching , data integration , semantic matching , semantic integration , Wiktionary
Abstract: This paper presents the results of the Wiktionary Matcher in the Ontology Alignment Evaluation Initiative(OAEI) 2020.Wiktionary Matcher is an ontology matching tool that exploits Wiktionary as external background knowledge source. Wiktionary is a large lexical knowledge resource that is collaboratively built online. Multiple current language versions of Wiktionary are merged and used for monolingual ontology matching by exploiting synonymy relations and for multilingual matching by exploiting the translations given in the resource. This is the second OAEI participation of the matching system. Wiktionary Matcher has been improved and is the best performing system on the knowledge graph track this year.

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