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|Create Date||December 14, 2015|
An efficient way to evaluate FCA algorithms is through a comparative analysis of their performance in typical contexts. Comparisons are normally conducted using randomly generated contexts that may contain duplicated attributes and objects and other types of redundancies. Failing to acknowledge the presence of these redundancies in formal contexts could lead to erroneous comparison analysis. This tool named SCGaz (Synthetic Context Generator) that randomly fills synthetic formal contexts ensuring the absence of some type of redundancies. At the same time, the tool is able to keep track of the contexts density, allowing users to select any density in the bounds of the minimum and maximum permitted for a type of context. Thus, this approach allows more controllable and reliable simulation environment.
Reference for citation:
RIMSA, ANDREI ; SONG, MARK A.J. ; ZARATE, LUIS E. SCGaz - A Synthetic Formal Context Generator with Density Control for Test and Evaluation of FCA Algorithms. In: 2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013), 2013, Manchester. 2013 IEEE International Conference on Systems, Man, and Cybernetics. v. 1. p. 3464-7.