Knowledge recommendation for product development using integrated rough set-information entropy correction

2020 ◽  
Vol 31 (6) ◽  
pp. 1559-1578 ◽  
Author(s):  
Zhenyong Wu ◽  
Lina He ◽  
Yuan Wang ◽  
Mark Goh ◽  
Xinguo Ming
Keyword(s):  
Product Development ◽  
Rough Set ◽  
Information Entropy ◽  
Entropy Correction

THE INFORMATION ENTROPY, ROUGH ENTROPY AND KNOWLEDGE GRANULATION IN ROUGH SET THEORY

2004 ◽  
Vol 12 (01) ◽  
pp. 37-46 ◽  
Author(s):  
JIYE LIANG ◽  
ZHONGZHI SHI
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Information Entropy ◽  
Granular Computing ◽  
Rough Set Theory ◽  
Computer Applications ◽  
Mathematical Tool

Rough set theory is a relatively new mathematical tool for use in computer applications in circumstances which are characterized by vagueness and uncertainty. In this paper, we introduce the concepts of information entropy, rough entropy and knowledge granulation in rough set theory, and establish the relationships among those concepts. These results will be very helpful for understanding the essence of concept approximation and establishing granular computing in rough set theory.

The Discretization Algorithm Based on Rough Set and its Application

2013 ◽  
Vol 416-417 ◽  
pp. 1399-1403 ◽  
Author(s):  
Zhi Cai Shi ◽  
Yong Xiang Xia ◽  
Chao Gang Yu ◽  
Jin Zu Zhou
Keyword(s):  
Intrusion Detection ◽  
Set Theory ◽  
Rough Set ◽  
Information Entropy ◽  
Rough Set Theory ◽  
Information Loss ◽  
Intrusion Detection Systems ◽  
Detection Systems ◽  
Discretization Algorithm ◽  
Response Performance

The discretization is one of the most important steps for the application of Rough set theory. In this paper, we analyzed the shortcomings of the current relative works. Then we proposed a novel discretization algorithm based on information loss and gave its mathematical description. This algorithm used information loss as the measure so as to reduce the loss of the information entropy during discretizating. The algorithm was applied to different samples with the same attributes from KDDcup99 and intrusion detection systems. The experimental results show that this algorithm is sensitive to the samples only for parts of all attributes. But it dose not compromise the effect of intrusion detection and it improves the response performance of intrusion detection remarkably.

Review on Application of Rough Set Theory

2013 ◽  
Vol 694-697 ◽  
pp. 2905-2909
Author(s):  
Hua Yan
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Information Entropy ◽  
Rough Set Theory ◽  
Attribute Reduction ◽  
Great Development

Rough set theory has found an increasingly wide utilization since it was promoted in 1980s.And study on the application of rough set theory in every field has a great development in recent years. Application of rough set theory in attribute reduction, continuous attributes discretization, and uncertainty measuring, as well as application of information entropy in rough set theory are reviewed in this paper. What we will do next is to probe further into the application of information entropy in rough set theory.

Complement information entropy for uncertainty measure in fuzzy rough set and its applications

2014 ◽  
Vol 19 (7) ◽  
pp. 1997-2010 ◽  
Author(s):  
Junyang Zhao ◽  
Zhili Zhang ◽  
Chongzhao Han ◽  
Zhaofa Zhou
Keyword(s):  
Rough Set ◽  
Information Entropy ◽  
Uncertainty Measure ◽  
Fuzzy Rough Set
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