Finding association rules in semantic web data
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comunitat-uji-handle2:10234/7038
comunitat-uji-handle3:10234/8634
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http://dx.doi.org/10.1016/j.knosys.2011.05.009 |
Metadata
Title
Finding association rules in semantic web dataDate
2012-02Publisher
ElsevierISSN
0950-7051Type
info:eu-repo/semantics/articlePublisher version
http://www.sciencedirect.com/science/article/pii/S0950705111001031Subject
Abstract
The amount of ontologies and semantic annotations available on the Web is constantly growing. This new type of complex and heterogeneous graph-structured data raises new challenges for the data mining community. In ... [+]
The amount of ontologies and semantic annotations available on the Web is constantly growing. This new type of complex and heterogeneous graph-structured data raises new challenges for the data mining community. In this paper, we present a novel method for mining association rules from semantic instance data repositories expressed in RDF/(S) and OWL. We take advantage of the schema-level (i.e. Tbox) knowledge encoded in the ontology to derive appropriate transactions which will later feed traditional association rules algorithms. This process is guided by the analyst requirements, expressed in the form of query patterns. Initial experiments performed on semantic data of a biomedical application show the usefulness and efficiency of the approach. [-]
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Knowledge-Based Systems, 25, 1Rights
(c) 2011 Elsevier B.V. All rights reserved
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- LSI_Articles [362]