Applying Attribute Exploration Algorithms to Knowledge Discovery
Quan Yu
Abstract
Quan Yu
Abstract
From a artificial intelligence viewpoint,In a specific knowledge domain,all the objects and attributes make up a formal context of itself.If its attribute set is finite,but the cardinality of object set is very large or even is infinite in the formal context of this knowledge domain.In this paper,We design the extending attribute exploration algorithms,which can find out the Duquenne-Guigues base of the specific knowledge domain,and then we show the function of the algorithms by an example.
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From a artificial intelligence viewpoint,In a specific knowledge domain,all the objects and attributes make up a formal context of itself.If its attribute set is finite,but the cardinality of object set is very large or even is infinite in the formal context of this knowledge domain.In this paper,We design the extending attribute exploration algorithms,which can find out the Duquenne-Guigues base of the specific knowledge domain,and then we show the function of the algorithms by an example.
Key concepts: Cardinality (data modeling), Computer science, Domain (mathematical analysis), Knowledge base, Context (archaeology), Attribute domain, Domain knowledge, Set (abstract data type)