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Modeling human newspaper readers: The Fuzzy Believer approach

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TitleModeling human newspaper readers: The Fuzzy Believer approach
Publication TypeJournal Article
Year of Publication2014
AuthorsKrestel, R., S. Bergler, and R. Witte
Refereed DesignationRefereed
JournalNatural Language Engineering
Volume20
Issue02
Pagination261–288
Date PublishedApril 2014
KeywordsArtificial Believer, Fuzzy Believer, Fuzzy NLP, Textual Entailment Recognition
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.

URLhttp://journals.cambridge.org/repo_A91w9lhA
DOI10.1017/S1351324912000289
Copyright

Copyright © Cambridge University Press 2012.

Impact Factor

0.474 (2012)

History

Received: February 06, 2012
Revised: September 06, 2012
Accepted: September 07, 2012
Published Online: October 12, 2012

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nle_fuzzy_believer.pdf313.8 KB