Generalized one-sided concept lattices (GOSCL) represent an FCA-like method for analysis of object-attribute models with different types of attributes. Since the number of concepts can be exponential with respect to the number of objects in a model, study of various reduction methods represents one of the most recognized problems in FCA.
One of such reduction is possible, provided that a Moore co-family on object set is considered as some kind of parameter. In order to investigate the efficiency of such reduction method, we experimentally study a reduction ratio for randomly generated contexts.