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Ontology Discovery for the Semantic Web Using Hierarchical Clustering |
Clerkin, Patrick; Cunningham, Padraig; Hayes, Conor
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TCD-CS-2002-25 According to a proposal by Tim Berners-Lee, the World Wide Web
should be extended to make a Semantic Web where human understandable
content is structured in such a way as to make it machine processable. Central
to this conception is the establishment of shared ontologies, which specify the
fundamental objects and relations important to particular online communities.
Normally, such ontologies are hand crafted by domain experts. In this paper we
propose that certain techniques employed in data mining tasks can be adopted
to automatically discover and generate ontologies. In particular, we focus on the
conceptual clustering algorithm, COBWEB, and show that it can be used to
generate class hierarchies expressible in RDF Schema. We consider
applications of this approach to online communities where recommendation of
assets on the basis of user behaviour is the goal, illustrating our arguments with
reference to the Smart Radio online song recommendation application.
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Keyword(s):
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Computer Science |
Publication Date:
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2002 |
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Type:
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Report |
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Peer-Reviewed:
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Unknown |
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Language(s):
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English |
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Institution:
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Trinity College Dublin |
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Citation(s):
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Clerkin, Patrick; Cunningham, Padraig; Hayes, Conor. 'Ontology Discovery for the Semantic Web Using Hierarchical Clustering'. - Dublin, Trinity College Dublin, Department of Computer Science, TCD-CS-2002-25, 2002, pp12 |
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Publisher(s):
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Trinity College Dublin, Department of Computer Science |
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File Format(s):
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application/pdf |
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First Indexed:
2014-05-13 05:31:18 Last Updated:
2015-04-10 05:14:02 |
