The knowledge graph track at OAEI : Gold standards, baselines, and the golden hammer bias


Hertling, Sven ; Paulheim, Heiko


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DOI: https://doi.org/10.1007/978-3-030-49461-2_20
URL: https://madoc.bib.uni-mannheim.de/54181
Additional URL: https://link.springer.com/chapter/10.1007/978-3-03...
URN: urn:nbn:de:bsz:180-madoc-541815
Document Type: Conference or workshop publication
Year of publication: 2020
Book title: The semantic web : 17th international conference, ESWC 2020, Heraklion, Crete, Greece, May 31-June 4, 2020 : proceedings
Page range: 343-359
Conference title: ESWC 2020
Location of the conference venue: Online
Date of the conference: 31.05.-04.06.2020
Publisher: Harth, Andreas
Place of publication: Cham
Publishing house: Springer
ISBN: 978-3-030-49460-5 , 978-3-030-49461-2
Publication language: English
Institution: School of Business Informatics and Mathematics > Web Data Mining (Paulheim 2018-)
Subject: 004 Computer science, internet
Keywords (English): Ontology Matching , Instance Matching , Knowledge Graph
Abstract: The Ontology Alignment Evaluation Initiative (OAEI) is an annual evaluation of ontology matching tools. In 2018, we have started the Knowledge Graph track, whose goal is to evaluate the simultaneous matching of entities and schemas of large-scale knowledge graphs. In this paper, we discuss the design of the track and two different strategies of gold standard creation. We analyze results and experiences obtained in first editions of the track, and, by revealing a hidden task, we show that all tools submitted to the track (and probably also to other tracks) suffer from a bias which we name the golden hammer bias.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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