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8篇 您的检索式：作者名="Kaiquan Xu"

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		题名	作者	年代	出处	被引量
	1	F-Law collision and system state recognition显示文摘Using function one direction S-rough sets (function one direction singular rough sets), f-law and F-law and the concept of law distance and the concept of system law collided by F-law are given. Using these concepts, state characteristic presented by system law collided by F-law and recognition of these states characteristic and recognition criterion and applications are given. Function one direction S-rough sets is one of basic forms of function S-rough sets (function singular rough sets). Function one direction S-rough sets is importance theory and is a method in studying system law collision.	Shi Kaiquan Xu Xiaojing	2007	Journal of Systems Engineering and Electronics2007，18，2：	4
	2	Mining comparative o- pinions from customer reviews for competitive intelligence显示文摘	Xu Kaiquan Liao Shaoyi Li Jiexun	2011	De- cision Support Systems2011，50，8：	1
	3	Mining comparative o- pinions from customer reviews for competitive intelligence 显示文摘	Xu Kaiquan Liao Shaoyi Li Jiexun	2011	De- cision Support Systems2011，50，4：	1
	4	P-sets and applications of internal outer data circle显示文摘	Zhang Li Xu Ming Shi Kaiquan	2010	Quantitative Logic and Soft Computing2010，2，：	1
	5	Mining comparative opinions from customer reviews for Competitive Intelligence 显示文摘	Xu Kaiquan Liao Stephen Shaoyi Li Jiexun	2011	DecisionSupport Systems2011，50，4：	1
	6	Mining Compara- tive Opinions from Customer Reviews for Competitive Intelli- gence Original Research Articl 显示文摘	Kaiquan Xu Stephen Shaoyi Liao Jiexun Li	2011	Decision Support Systems2011，4，50：	1
	7	Static rough similarity degree and its applications显示文摘The definition of rough similarity degree is given based on the axiomatic similarity degree, and the properties of rough similarity degree are listed. Using the properties of rough similarity degree, the method of clustering in rough systems can be obtained. After clustering, a new sample can be recognized by the principle of maximal rough similarity degree.	Xu Xiaojing Li Jian Shi Kaiquan	2008	Journal of Systems Engineering and Electronics2008，19，2：	0
	8	Rough similarity degree and rough close degree in rough fuzzy sets and the applications显示文摘Based on rough similarity degree of rough sets and close degree of fuzzy sets, the definitions of rough similarity degree and rough close degree of rough fuzzy sets are given, which can be used to measure the similar degree between two rough fuzzy sets. The properties and theorems are listed. Using the two new measures, the method of clustering in the rough fuzzy system can be obtained. After clustering, the new fuzzy sample can be recognized by the principle of maximal similarity degree.	Li Jian Xu Xiaojing Shi Kaiquan	2008	Journal of Systems Engineering and Electronics2008，19，5：	0

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