Title :
Algorithms on Discretizing Continuous Attributes Values and Its Application to Synthetical Test and Evaluation of Patent Strength
Author :
Zeng, Minghua ; Pan, Xiongfeng ; Liu, Qing
Author_Institution :
Dept. of Sci., Nanchang Inst. of Technol.
Abstract :
Rough set theory is one of the excellent methods to deal with the uncertain and incomplete information of discrete attributes values. This paper firstly constructs an algorithm to discretize continuous attributes values based on fuzzy similarity relation, and then proposes an algorithm for synthesis evaluation of decision-making tables based on rough set theory, which is integrated with the weight computing technique in AHP but does not use judgment matrix. Both of the algorithms are used to analyze synthetically the patent strength of the eight economic zones in Chinese mainland. Numerical experimental results show that the proposed algorithms are efficient, effective and feasible
Keywords :
data mining; fuzzy reasoning; patents; rough set theory; China; continuous attribute value discretization; decision-making tables; fuzzy similarity relation; incomplete information; patent strength evaluation; rough set theory; synthetical test; uncertain information; Algorithm design and analysis; Application software; Computer science; Decision making; Decision support systems; Fuzzy set theory; Pattern recognition; Power generation economics; Set theory; Testing;
Conference_Titel :
Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2702-7
DOI :
10.1109/ICDMW.2006.25