Um Arcabouço para Desenvolvimento de Algoritmos da Análise Formal de Conceitos

This paper presents a framework for the development of formal concept analysis (FCA) algorithms. Its main component is a synthetic generator which formal parameters can be adjusted to allow testing the algorithms in situations of interest. It is also presented in the framework some basic FCA algorithms and some formal contexts obtained from real data sets, from a relatively small to a very large, the latter usually impractical at original form. To illustrate the algorithms performance evaluation via the framework, some basic algorithms are evaluated using synthetic and real data sets. Originally developed to serve as a tool to support the learning of the main FCA algorithms, there is nothing to prevent the framework from being used in the evaluation of new algorithms. For this, it’s of particular importance the fact that the data generation parameters are adjustable to cover situations of interest.