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Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title Adding data mining support to SPARQL via statistical relational learning methods
Organization Unit
Authors
  • C Kiefer
  • Abraham Bernstein
  • A Locher
Editors
  • S Bechhofer
  • M Hauswirth
  • J Hoffmann
  • M Koubarakis
Presentation Type paper
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
ISBN 978-3-540-68233-2
Page Range 478 - 492
Event Title 5th European Semantic Web Conference (ESWC)
Event Type conference
Event Location Tenerife, Spain
Event Start Date June 1 - 2008
Event End Date June 5 - 2008
Series Name Lecture Notes in Computer Science (LNCS)
Number 5021
Place of Publication Berlin
Publisher Springer
Abstract Text Exploiting the complex structure of relational data enables to build better models by taking into account the additional information provided by the links between objects. We extend this idea to the Semantic Web by introducing our novel SPARQL-ML approach to perform data mining for Semantic Web data. Our approach is based on traditional SPARQL and statistical relational learning methods, such as Relational Probability Trees and Relational Bayesian Classifiers. We analyze our approach thoroughly conducting three sets of experiments on synthetic as well as real-world data sets. Our analytical results show that our approach can be used for any Semantic Web data set to perform instance-based learning and classification. A comparison to kernel methods used in Support Vector Machines shows that our approach is superior in terms of classification accuracy.
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Digital Object Identifier 10.1007/978-3-540-68234-9_36
Other Identification Number merlin-id:347
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Additional Information In this book, the proceedings of the 5th European Semantic Web Conference (ESWC 2008), Tenerife, Canary Islands, Spain, June 1-5, 2008 are published, at which this paper was presented. The original publication is available at www.springerlink.com