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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2018
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th-cmuir.6653943832-436752018-04-25T07:21:16Z Uncertain information fusion and knowledge integration: How to take reliability into account Hung T. Nguyen Kittawit Autchariyapanitkul Olga Kosheleva Vladik Kreinovich Computer Science Mathematics Agricultural and Biological Sciences © 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. 2018-01-24T03:51:58Z 2018-01-24T03:51:58Z 2017-08-30 Conference Proceeding 2-s2.0-85030837585 10.1109/IFSA-SCIS.2017.8023348 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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Computer Science Mathematics Agricultural and Biological Sciences |
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Computer Science Mathematics Agricultural and Biological Sciences Hung T. Nguyen Kittawit Autchariyapanitkul Olga Kosheleva Vladik Kreinovich Uncertain information fusion and knowledge integration: How to take reliability into account |
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© 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. |
| format |
Conference Proceeding |
| author |
Hung T. Nguyen Kittawit Autchariyapanitkul Olga Kosheleva Vladik Kreinovich |
| author_facet |
Hung T. Nguyen Kittawit Autchariyapanitkul Olga Kosheleva Vladik Kreinovich |
| author_sort |
Hung T. Nguyen |
| title |
Uncertain information fusion and knowledge integration: How to take reliability into account |
| title_short |
Uncertain information fusion and knowledge integration: How to take reliability into account |
| title_full |
Uncertain information fusion and knowledge integration: How to take reliability into account |
| title_fullStr |
Uncertain information fusion and knowledge integration: How to take reliability into account |
| title_full_unstemmed |
Uncertain information fusion and knowledge integration: How to take reliability into account |
| title_sort |
uncertain information fusion and knowledge integration: how to take reliability into account |
| publishDate |
2018 |
| url |
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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