Uncertain information fusion and knowledge integration: How to take reliability into account

© 2017 IEEE. In many practical situations, we need to fuse and integrate information and knowledge from different sources - and do it under uncertainty. Most existing methods for information fusion and knowledge integration take into account uncertainty. In addition to uncertainty, we also face the...

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Bibliographic Details
Main Authors: Hung T. Nguyen, Kittawit Autchariyapanitkul, Olga Kosheleva, Vladik Kreinovich
Format: Conference Proceeding
Published: 2018
Subjects:
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85030837585&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/43675
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Institution: Chiang Mai University
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Summary:© 2017 IEEE. In many practical situations, we need to fuse and integrate information and knowledge from different sources - and do it under uncertainty. Most existing methods for information fusion and knowledge integration take into account uncertainty. In addition to uncertainty, we also face the problem of reliability: sensors may malfunction, experts can be wrong, etc. In this paper, we show how to take into account both uncertainty and reliability in information fusion and knowledge integration. We show this on the examples of probabilistic and fuzzy uncertainty.