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Semantic Software Lab
Concordia University
Montréal, Canada

Fuzzy Set Theory-Based Belief Processing for Natural Language Texts

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TitleFuzzy Set Theory-Based Belief Processing for Natural Language Texts
Publication TypeConference Paper
Year of Publication2007
AuthorsKrestel, R., R. Witte, and S. Bergler
Refereed DesignationRefereed
Conference NameProceedings of the Twenty-Second AAAI Conference on Artificial Intelligence (AAAI)
Date PublishedJuly 22–26
PublisherAAAI Press
Conference LocationVancouver, British Columbia, Canada
Type of WorkPoster
ISBN Number978-1-57735-323-2

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 artificial believer system we present in this paper is to extract and analyze opinionated statements from newspaper articles.

Beliefs are modeled with a fuzzy-theoretic approach applied after NLP-based information extraction. A fuzzy believer models a human agent, deciding what statements to believe or reject based on different, configurable strategies.


Copyright © 2007 AAAI Press. It is posted here by permission of AAAI for your personal use. Not for redistribution.

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