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ASME Press Select Proceedings
International Conference on Electronics, Information and Communication Engineering (EICE 2012)
By
Garry Lee
Garry Lee
Information Engineering Research Institute
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ISBN:
9780791859971
No. of Pages:
1008
Publisher:
ASME Press
Publication date:
2012

The uncertain knowledge representation and reasoning are the hotspot and core of artificial intelligence research. In the paper a unified framework for representing, reasoning and learning of uncertain information is put forward. The abstract degree is used to measure the uncertain degree of uncertain information and thus more powerful expressive capacity is attained. Moreover the framework supports the efficient acquisition of the uncertain information, and concept abstract degree is used to describe the conceptual hierarchic in concept space. These features make the framework more practical than existing theories of reasoning about uncertainty.

Abstract
Keywords
Preface
Concept Space
Knowledge Representation Based on Concept Cell
Activating Rule for Concept Cell
The Structure for Reasoning
Conclusion
References
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