Ralf Krestel

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AAAI 07

Fuzzy Set Theory-Based Belief Processing for Natural Language Texts

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 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.

Poster Paper

AAAI07.pdf

Conference Homepage

AAAI-07

BibTex Entry

@InProceedings{krestel-aaai07, author = {Ralf Krestel and Ren\'{e} Witte and Sabine Bergler}, title = {{Fuzzy Set Theory-Based Belief Processing for Natural Language Texts}}, booktitle = {AAAI'07: Proceedings of the 22nd national conference on Artificial intelligence}, isbn = {978-1-57735-323-2}, pages = {1878--1879}, location = {Vancouver, British Columbia, Canada}, month = {July 22--26}, year = {2007}, publisher = {AAAI Press} }