12,000

We have over 12,000 students, from over 100 countries, within one of the safest campuses in the UK

93%

93% of Lancaster students go into work or further study within six months of graduating

Home > Research > Publications & Outputs > Learning to Classify Identity Web References Us...
View graph of relations

Keywords

« Back

Learning to Classify Identity Web References Using RDF Graphs

Research output: Contribution to conferencePoster

Published

Publication date2009
Number of pages2
Original languageEnglish

Other

OtherPoster Track of the International Semantic Web Conference 2009
CountryUnited States
Period20/10/09 → …

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.