Voting-based Methods for Evaluating Sources and Facts Reliability

被引:0
|
作者
Elsaesser, Quentin [1 ]
Everaere, Patricia [2 ]
Konieczny, Sebastien [1 ]
机构
[1] Univ Artois, CNRS, CRIL, Lens, France
[2] Univ Lille, CNRS, CRIStAL, Lille, France
来源
2023 IEEE 35TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, ICTAI | 2023年
关键词
Reliability; Truth Tracking; Voting; Trust;
D O I
10.1109/ICTAI59109.2023.00034
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this work we propose a family of methods that allow to conjointly compute the reliability of a set of information sources and the confidence of the facts on a set of objects, by confronting the sources points of view. We use a (scoring-based) voting method for the evaluation of the trust of the sources, using Condorcet's Jury Theorem arguments in order to identify the truth and the reliable sources. We discuss general theoretical properties that such operators should satisfy, and we study what are the properties satisfied by our methods. We provide an experimental study that shows that we perform better than state of the art methods on the task of finding the truth among the possible facts. We show that we can also adequately evaluate the reliability of the sources of information.
引用
收藏
页码:178 / 185
页数:8
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