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Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-8936

Kiefer, C; Bernstein, A; Locher, A (2008). Adding data mining support to SPARQL via statistical relational learning methods. In: 5th European Semantic Web Conference (ESWC), Tenerife, Spain, 1 June 2008 - 5 June 2008, 478-492.

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Abstract

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.

Citations

8 citations in Web of Science®
10 citations in Scopus®
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155 downloads since deposited on 09 Jan 2009
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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
DDC:000 Computer science, knowledge & systems
Language:English
Event End Date:5 June 2008
Deposited On:09 Jan 2009 08:30
Last Modified:09 Jul 2012 03:31
Publisher:Springer
Series Name:Lecture Notes in Computer Science (LNCS)
Number:5021
ISBN:978-3-540-68233-2
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
Publisher DOI:10.1007/978-3-540-68234-9_36
Official URL:http://www.ifi.uzh.ch/pax/web/index.php/publication/show/id/824
Related URLs:http://www.eswc2008.org

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