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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 |
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Editors |
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Presentation Type | paper |
Item Subtype | Original Work |
Refereed | Yes |
Status | Published in final form |
Language |
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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. |
Related URLs | |
Digital Object Identifier | 10.1007/978-3-540-68234-9_36 |
Other Identification Number | merlin-id:347 |
PDF File | Download from ZORA |
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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 |