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Modeling human newspaper readers: The Fuzzy Believer approach

Published online by Cambridge University Press:  12 October 2012

RALF KRESTEL ,
SABINE BERGLER  and
RENÉ WITTE
RALF KRESTEL
Affiliation:
Department of Computer ScienceUniversity of California, Irvine, CA, USA e-mail: krestel@uci.edu
SABINE BERGLER
Affiliation:
Department of Computer Science and Software EngineeringConcordia University, Montréal, Canada e-mail: bergler@cse.concordia.ca, rwitte@cse.concordia.ca
RENÉ WITTE
Affiliation:
Department of Computer Science and Software EngineeringConcordia University, Montréal, Canada e-mail: bergler@cse.concordia.ca, rwitte@cse.concordia.ca
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Abstract

The growing number of publicly available information sources makes it impossible for individuals to keep track of all the various opinions on one topic. The goal of our Fuzzy Believer system presented in this paper is to extract and analyze statements of opinion from newspaper articles. Beliefs are modeled using the fuzzy set theory, applied after Natural Language Processing-based information extraction. The Fuzzy Believer models a human agent, deciding what statements to believe or reject based on a range of configurable strategies.

Type
Articles
Information
Natural Language Engineering , Volume 20 , Issue 2 , April 2014 , pp. 261 - 288
Copyright
Copyright © Cambridge University Press 2012 

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