Cluster analysis of dialogs with transport directory service allows revealing the typical scenarios of dialogs, which is useful for designing automatic dialog systems. We show how to parameterize dialogs and how to control the process of clustering. The parameters include both data of transport service and features of passenger’s behavior. Control of clustering consists in manipulating the parameter’s weights and checking stability of the results. This technique resembles Makagonov’s approach to the analysis of dweller’s complaints to city administration. We shortly describe the MajorClust method developped by Benno Stein’s group and demonstrate its work on real person-toperson dialogs provided by Spanish railway service.