Analysis Of Interval-valued Decision Formal Contexts

The theory of concept lattice, also called formal concept analysis, proposed by the German mathematician Wille R. in1982, is a highly efficient processing mathematical tool of data analysis and knowledge discovery. It is perfect in theory, widely extended in application since the1990s, and further, it has gradually become an important research object of artificial intelligence discipline. At present, the theory of concept lattice has been widely applied in data mining, knowledge acquisition, information retrieval, machine learning, granular computing, software engineering and other fields.Classic formal concept analysis is mainly dealing with single valued formal context, but in the real world, because of the complexity of the issue, attribute value tends to be continuous, therefore,it will be easier to describe complex data and uncertainty of practical problems by using interval-valued.This paper constructes the large interval-valued concepts and their large interval-valued concept lattices based on interval-valued formal context, and gives an approach to attribute reduct of large interval-valued concept lattices; On the basis of classical consistent decision formal context, we introduce consistent interval-valued decision formal context, and discuss the problems of attribute reduction and rule acquisition in consistent interval-valued decision formal context; we formulate a new knowledge reduction framework in interval-valued decision formal contexts from the perspective of rule acquisition, and also can derive more compact decision rules from the reduced interval-valued decision formal context.