An Innovative Approach for Attribute Reduction in Rough Set Theory

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Intelligent Information Management

ISSN Print: 2160-5912
ISSN Online: 2160-5920
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"An Innovative Approach for Attribute Reduction in Rough Set Theory"
written by Alex Sandro Aguiar Pessoa, Stephan Stephany,
published by Intelligent Information Management, Vol.6 No.5, 2014

has been cited by the following article(s):

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[1]	One-to-one marketing management via customer complaint
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[2]	Data Mining Approaches to the Real-Time Monitoring and Early Warning of Convective Weather Using Lightning Data
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[3]	Faults Repairing Analysis Using Rough Sets after Implementation of Labor Force Redistribution Algorithm: A Case Study in Telecom Egypt
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[4]	Analysis of faults fixing system using rough sets: A case study in large-scale telecommunication company (telecom egypt)
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[5]	Rough set theory and three way decisions: Refinement of boundary region in the decision making process
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[6]	An Approach of Factor Screening in Multifactor Mixture Experiments using Rough Set Theory
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[7]	Algorithm of Attribute Reduction in Dominance Based Rough Sets Combined with Dominance Discernibility Matrix
	ICIMCS 2016 Proceedings of the International Conference on Internet Multimedia Computing and Service, 2016

[8]	A comprehensive and heuristic approach for Personalized Web Search using Greedy Algorithm
	International Research Journal of Engineering and Technology, 2016

[9]	Meteorological data mining for climate precipitation prediction using neural networks
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[10]	A survey: Rough set theory in incomplete information systems
	2015

[1]	One-to-one marketing management via customer complaint Social Network Analysis and Mining, 2023 DOI:10.1007/s13278-023-01082-z

[2]	One-to-one marketing management via customer complaint Social Network Analysis and Mining, 2023 DOI:10.1007/s13278-023-01082-z

[3]	Analysis of faults fixing system using rough sets: A case study in large-scale telecommunication company (telecom egypt) 2017 13th International Computer Engineering Conference (ICENCO), 2017 DOI:10.1109/ICENCO.2017.8289822

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