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Learning to Classify Identity Web References Using RDF Graphs

Research output: Contribution to conference - Without ISBN/ISSN Posterpeer-review

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Learning to Classify Identity Web References Using RDF Graphs. / Rowe, Matthew; Iria, Jose.
2009. Poster session presented at Poster Track of the International Semantic Web Conference 2009, United States.

Research output: Contribution to conference - Without ISBN/ISSN Posterpeer-review

Harvard

Rowe, M & Iria, J 2009, 'Learning to Classify Identity Web References Using RDF Graphs', Poster Track of the International Semantic Web Conference 2009, United States, 20/10/09. <http://kcap09.stanford.edu/share/posterDemos/154/paper154.pdf>

APA

Rowe, M., & Iria, J. (2009). Learning to Classify Identity Web References Using RDF Graphs. Poster session presented at Poster Track of the International Semantic Web Conference 2009, United States. http://kcap09.stanford.edu/share/posterDemos/154/paper154.pdf

Vancouver

Rowe M, Iria J. Learning to Classify Identity Web References Using RDF Graphs. 2009. Poster session presented at Poster Track of the International Semantic Web Conference 2009, United States.

Author

Rowe, Matthew ; Iria, Jose. / Learning to Classify Identity Web References Using RDF Graphs. Poster session presented at Poster Track of the International Semantic Web Conference 2009, United States.2 p.

Bibtex

@conference{8771335f0b4e496ba4d02326d56ebae0,
title = "Learning to Classify Identity Web References Using RDF Graphs",
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.",
keywords = "Semantic web",
author = "Matthew Rowe and Jose Iria",
year = "2009",
language = "English",
note = "Poster Track of the International Semantic Web Conference 2009 ; Conference date: 20-10-2009",

}

RIS

TY - CONF

T1 - Learning to Classify Identity Web References Using RDF Graphs

AU - Rowe, Matthew

AU - Iria, Jose

PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

KW - Semantic web

M3 - Poster

T2 - Poster Track of the International Semantic Web Conference 2009

Y2 - 20 October 2009

ER -