Nikolov, Andriy; Uren, Victoria and Motta, Enrico
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Schema-level heterogeneity represents an obstacle for automated discovery of coreference resolution links between individuals. Although there is a multitude of existing schema matching solutions, the Linked Data environment differs from the standard scenario assumed by these tools. In particular, large volumes of data are available, and repositories are connected into a graph by instance-level mappings. In this paper we describe how these features can be utilised to produce schema-level mappings which facilitate the instance coreference resolution process. Initial experiments applying this approach to public datasets have produced encouraging results.
|Item Type:||Conference Item|
|Copyright Holders:||2010 The Authors|
|Extra Information:||CEUR Workshop Proceedings Vol.628
LDOW-2010 Linked Data on the Web 2010
Proceedings of the WWW2010 Workshop on Linked Data on the Web
Raleigh, USA, April 27, 2010.
Edited by Christian Bizer; Tom Heath; Tim Berners-Lee; Michael Hausenblas
|Keywords:||data fusion; coreference resolution; linked data|
|Academic Unit/Department:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Interdisciplinary Research Centre:||Centre for Research in Computing (CRC)|
|Depositing User:||Kay Dave|
|Date Deposited:||19 Aug 2011 09:09|
|Last Modified:||05 Oct 2016 11:06|
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