Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06) Algorithms on Discretizing Continuous Attributes Values and Its Application to Synthetical Test and Evaluation of Patent Strength Hong Kong, China December 18-December 22 ISBN: 0-7695-2702-7
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDMW.2006.25
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.
Citation:
Minghua Zeng, Xiongfeng Pan, Qing Liu, "Algorithms on Discretizing Continuous Attributes Values and Its Application to Synthetical Test and Evaluation of Patent Strength," icdmw, pp.428-432, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||