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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| Main Authors: | , , , |
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| 格式: | Conference Proceeding |
| 出版: |
2018
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| 主題: | |
| 在線閱讀: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85030837585&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/57066 |
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| 機構: | Chiang Mai University |
| 總結: | © 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. |
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