基于量化扩展概念格的属性归纳算法<sup>*</sup>

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Abstract In knowledge discovery in databases (KDD), users show much interest in highlevel, general and reductive information. Attribute oriented induction (AOI), which generally takes the statistical information from original data into account, has been commonly used in data reduction. However, attributeoriented algorithm based on quantitative concept lattice can finish induction with multilevel and multiattribute by using concept ascension according to the Hasse diagram of the quantitative extended concept lattice. Compared with AOI, the generalization path of the proposed algorithm is not unique. The proper generalization paths and thresholds on the Hasse diagram of quantitative extended concept lattice could be found easily. The required reasonable results are gotten, and different granular knowledge is provided for users.

Key words： Attribute Oriented Induction (AOI) Concept Lattice Concept Hierarchies Data Mining

Received: 20 April 2006

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	Articles by authors
	WANG DeXing
	HU XueGang
	L IU XiaoPing
	HUANG DongMei

Cite this article:

WANG DeXing,HU XueGang,L IU XiaoPing等. AttributeOriented Induction Algorithm Based on Quantitative Extended Concept Lattice[J]. , 2007, 20(6): 843-848.

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http://manu46.magtech.com.cn/Jweb_prai/EN/ OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2007/V20/I6/843

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