Analysis of Concept Drifting and Uncertainty in an Information Table

Deng Dayong; Miao Duoqian; Huang Houkuan

doi:10.7544/issn1000-1239.2016.20150803

Journal of Computer Research and Development > 2016 > 53(11): 2607-2612. > DOI: 10.7544/issn1000-1239.2016.20150803 CSTR: 32373.14.issn1000-1239.2016.20150803

Deng Dayong, Miao Duoqian, Huang Houkuan. Analysis of Concept Drifting and Uncertainty in an Information Table[J]. Journal of Computer Research and Development, 2016, 53(11): 2607-2612. DOI: 10.7544/issn1000-1239.2016.20150803

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Analysis of Concept Drifting and Uncertainty in an Information Table

¹(College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua, Zhejiang 321004)
²(School of Electronics and Information, Tongji University, Shanghai 201804)
³(School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044)
⁴(Xingzhi College, Zhejiang Normal University, Jinhua, Zhejiang 321004)

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Published Date: October 31, 2016

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Abstract

Abstract

Concept drifting detection is one of hot topics in data stream mining, and analysis of uncertainty is dominant in rough set theory. Combined with the ideas of data stream, concept drifting, rough sets and F-rough sets, a lot of concepts such as concept drifting of upper approximation, concept drifting of lower approximation, concept coupling of upper approximation and concept coupling of lower approximation etc are defined. The change of concepts in an information system is analyzed with these definitions. With the positive region, integral concept drifting, integral concept coupling are defined. The analysis and measurement for the change of concept uncertainty are conducted. From the view of epistemology, the concept of cognition convergence is defined from the ways of idealism and realism. It provides heuristic information for realizing the world of human beings from the viewpoints of granular computing and rough sets.
- rough sets,
- concept drift,
- attribute reduction,
- concept coupling,
- upper and lower approximation

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