Ordering objects via attribute preferences

We apply recent results on the construction of suitable orderings for the existence of right adjoint to the analysis of the following problem: given a preference ordering on the set of attributes of a given context, we seek an induced preference among the objects which is compatible with the information provided by the context.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Use of Concept Lattices for Data Tables with Different Types of Attributes

In this paper we describe the application of Formal Concept Analysis (FCA) for analysis of data tables with different types of attributes. FCA represents one of the conceptual data mining methods. The main limitation of FCA in classical case is the exclusive usage of binary attributes. More complex attributes then should be converted into binary tables. In our approach, called Generalized One-Sided Concept Lattices, we provide a method which deal with different types of attributes (e.g., ordinal, nominal, etc.) within one data table. Therefore, this method allows to create same FCA-based output in form of concept lattice with the precise many-valued attributes and the same interpretation of concept hierarchy as in the classical FCA, without the need for specific unified preprocessing of attribute values