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Learning to Classify Identity Web References Using RDF Graphs

Rowe, Matthew and Iria, Jose (2009) Learning to Classify Identity Web References Using RDF Graphs. In: Poster Track of the International Semantic Web Conference 2009, 2009-10-20.

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Abstract

The need to monitor a person's web presence has risen in recent years due to identity theft and lateral surveillance becoming prevalent web actions. In this paper we present a machine learning-inspired bootstrapping approach to monitor identity web references that only requires as input an initial small seed set of data modelled as an RDF graph. We vary the combination of different RDF graph matching paradigms with different machine learning classifiers and observe the effects on the classification of identity web references. We present preliminary results of an evaluation in order to show the variation in accuracy of these different permutations.

Item Type: Conference or Workshop Item (Poster)
Journal or Publication Title: Poster Track of the International Semantic Web Conference 2009
Uncontrolled Keywords: Semantic web
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 58316
Deposited By: ep_importer_pure
Deposited On: 28 Sep 2012 12:00
Refereed?: Yes
Published?: Published
Last Modified: 28 Sep 2012 12:00
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/58316

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