Visualizing and understanding large conceptual schemas requires the use ofspecific methods. These methods generate clustered, summarized, or focused schemasthat are easier to visualize and understand. All of these methods require computingthe importance of each entity type in the schema. In principle, the totality of knowledgedefined in the schema could be relevant for the computation of that importancebut, up to now, only a small part of that knowledge has been taken into account. Inthis paper, we extend seven existing methods for computing the importance of entitytypes by taking into account more relevant knowledge defined in the structural and behaviouralparts of the schema. We experimentally evaluate the original and extendedversions of these methods with three large real-world schemas. We present the twomain conclusions we have drawn from the experiments.