Leveraging terminological structure for object reconciliation

Noessner, Jan ; Niepert, Mathias ; Meilicke, Christian ; Stuckenschmidt, Heiner

DOI: https://doi.org/10.1007/978-3-642-13489-0_23
URL: https://link.springer.com/chapter/10.1007%2F978-3-...
Document Type: Conference or workshop publication
Year of publication: 2010
Book title: The Semantic Web: Research and Applications : 7th Extended Semantic Web Conference, ESWC 2010, Heraklion, Crete, Greece, May 30 – June 3, 2010, Proceedings, Part II
The title of a journal, publication series: Lecture Notes in Computer Science
Volume: 6089
Page range: 334-348
Conference title: ESWC 2010
Location of the conference venue: Heraklion, Greece
Date of the conference: 30.05.-03.06.2010
Publisher: Aroyo, Lora
Place of publication: Berlin [u.a.]
Publishing house: Springer
ISBN: 978-3-642-13488-3 , 978-3-642-13489-0
Publication language: English
Institution: School of Business Informatics and Mathematics > Praktische Informatik II (Stuckenschmidt 2009-)
Subject: 004 Computer science, internet
Abstract: It has been argued that linked open data is the major benefit of semantic technologies for the web as it provides a huge amount of structured data that can be accessed in a more effective way than web pages. While linked open data avoids many problems connected with the use of expressive ontologies such as the knowledge acquisition bottleneck, data heterogeneity remains a challenging problem. In particular, identical objects may be referred to by different URIs in different data sets. Identifying such representations of the same object is called object reconciliation. In this paper, we propose a novel approach to object reconciliation that is based on an existing semantic similarity measure for linked data. We adapt the measure to the object reconciliation problem, present exact and approximate algorithms that efficiently implement the methods, and provide a systematic experimental evaluation based on a benchmark dataset. As our main result, we show that the use of light-weight ontologies and schema information significantly improves object reconciliation in the context of linked open data.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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