Feature space theory in data mining: transformations between extensions and intensions in knowledge representation |
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| Authors: | Hong Xing Li Li Da Xu Jia Yin Wang Zhi Wen Mo |
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| Affiliation: | Tsinghua University, Beijing China, Sichuan Normal University, Chengdu , China, Beijing Normal University, China ;Old Dominion University, Norfolk, VA USA;Beijing Normal University, Beijing China;and Wright State University, Dayton, OH USA;Beijing Normal University, China;Sichuan Normal University, Chengdu , China |
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| Abstract: | Knowledge representation is one of the important topics in data mining research. In this paper, based on the feature space theory in data mining, the transformation between extensions and intensions of concepts is discussed in detail. First, inner projections of fuzzy relations, as a basic mathematical tool, are defined, and properties of inner projections are discussed. Then inner transformation of fuzzy relations, inverse inner transformations, and related properties are introduced. The concept structure is shown by feature spaces. Lastly, transformations between extensions and intensions are discussed. |
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| Keywords: | feature space knowledge representation extensions intensions inner projections fuzzy relation data mining |
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