Clustering of Attribute and/or Relational Data

A large class of clustering problems can be formulated as an optimizational prob-lem in which the best clustering is searched for among all feasible clustering accord-ing to a selected criterion function. This clustering approach can be applied to a va-riety of very interesting clustering problems, as it is possible to adapt it to a concrete clustering problem by an appropriate specification of the criterion function and/or by the definition of the set of feasible clusterings. Both, the blockmodeling problem (clustering of the relational data) and the clustering with relational constraint prob-lem (clustering of the attribute and relational data) can be very successfully treated by this approach. It also opens many new developments in these areas. The paired clustering approaches are applied to the Slovenian scientific collaboration data.