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Title: Ontology Discovery for the Semantic Web Using Hierarchical Clustering
Author: Clerkin, Patrick
Cunningham, Pádraig
Hayes, Conor
Keywords: Computer Science
Issue Date: Apr-2002
Publisher: Trinity College Dublin, Department of Computer Science
Citation: Clerkin, Patrick; Cunningham, Pádraig; 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
Series/Report no.: Computer Science Technical Report
Abstract: 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.
Appears in Collections:Computer Science Technical Reports

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