Formal Context Generation Using Dirichlet Distributions

Randomly generating formal contexts is an important task in the realm of formal concept analysis, in particular when comparing the performance of algorithms. We suggest an improved way to randomly generate formal contexts based on Dirichlet distributions. For this purpose we investigate the predominant method, coin-tossing, recapitulate some of its shortcomings and examine its stochastic model. Building upon this we propose our Dirichlet model and develop an algorithm employing this idea. Through an experimental evaluation we show that our approach is a significant improvement with respect to the variety of contexts generated.