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Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title Application and evaluation of inductive reasoning methods for the semantic web and software analysis
Organization Unit
  • Christoph Kiefer
  • Abraham Bernstein
Presentation Type paper
Item Subtype Original Work
Refereed Yes
Status Published in final form
  • English
ISBN 978-3-642-23031-8
ISSN 0203-9743 (P) 1611-3349 (E)
Page Range 460 - 503
Event Title Reasoning Web. Semantic Technologies for the Web of Data - 7th International Summer School 2011
Event Type other
Event Location Galway, Ireland
Event Start Date August 23 - 2011
Event End Date August 24 - 2011
Series Name Lecture Notes in Computer Science
Number 6848
Place of Publication 2011
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 four sets of experiments on synthetic as well as real-world data sets. Our analytical results show that our ap- proach can be used for almost any Semantic Web data set to perform instance-based learning and classification. A comparison to kernel methods used in Support Vector Machines even shows that our approach is superior in terms of classification accuracy.
Digital Object Identifier 10.1007/978-3-642-23032-5_10
Other Identification Number merlin-id:3615
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