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Leveraging terminological structure for object reconciliation
Noessner, Jan
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Niepert, Mathias
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Meilicke, Christian
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Stuckenschmidt, Heiner
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DOI:
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https://doi.org/10.1007/978-3-642-13489-0_23
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URL:
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https://link.springer.com/chapter/10.1007%2F978-3-...
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Document Type:
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Conference or workshop publication
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Year of publication:
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2010
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Book title:
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The Semantic Web: Research and Applications : 7th Extended Semantic Web Conference, ESWC 2010, Heraklion, Crete, Greece, May 30 – June 3, 2010, Proceedings, Part II
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The title of a journal, publication series:
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Lecture Notes in Computer Science
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Volume:
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6089
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Page range:
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334-348
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Conference title:
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ESWC 2010
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Location of the conference venue:
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Heraklion, Greece
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Date of the conference:
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30.05.-03.06.2010
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Publisher:
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Aroyo, Lora
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Place of publication:
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Berlin [u.a.]
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Publishing house:
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Springer
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ISBN:
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978-3-642-13488-3 , 978-3-642-13489-0
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ISSN:
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0302-9743 , 1611-3349
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Publication language:
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English
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Institution:
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School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
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Subject:
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004 Computer science, internet
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Abstract:
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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.
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 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
 Search Authors in
BASE:
Noessner, Jan
;
Niepert, Mathias
;
Meilicke, Christian
;
Stuckenschmidt, Heiner
Google Scholar:
Noessner, Jan
;
Niepert, Mathias
;
Meilicke, Christian
;
Stuckenschmidt, Heiner
ORCID:
Noessner, Jan, Niepert, Mathias, Meilicke, Christian  ORCID: https://orcid.org/0000-0002-0198-5396 and Stuckenschmidt, Heiner ORCID: https://orcid.org/0000-0002-0209-3859
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