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This method deals with representative-based supervised clustering, where a set of initial representatives is randomly chosen. One of the innovative aspects of SUWAN is that we use a supervised clustering algorithm to attributed networks that can be accomplished through a combination of weights between the matrix of distances of nodes and their attributes when defining the clusters. As a benchmark, we use Subgroup Discovery on attributed network data. Subgroup Discovery focuses on detecting subgroups described by specific patterns that are interesting with respect to some target concept and a set of explaining features. On the other hand, in order to analyze the impact of the network\u2019s topology on the group\u2019s performance, some network topology measures, and the group total turnover were exploited. The proposed methodologies are applied to an inter-organizational network, the EuroGroups Register, a central register that contains statistical information on business networks from European countries.<\/jats:p>","DOI":"10.3233\/ida-216436","type":"journal-article","created":{"date-parts":[[2023,4,7]],"date-time":"2023-04-07T15:36:29Z","timestamp":1680881789000},"page":"423-441","source":"Crossref","is-referenced-by-count":0,"title":["SUWAN: A supervised clustering algorithm with attributed networks"],"prefix":"10.1177","volume":"27","author":[{"given":"B\u00e1rbara","family":"Santos","sequence":"first","affiliation":[{"name":"Statistics Portugal, Lisbon, Portugal"},{"name":"Faculty of Economics, University of Porto, R. Dr. Roberto Frias, Porto, Portugal"}]},{"given":"Pedro","family":"Campos","sequence":"additional","affiliation":[{"name":"Statistics Portugal, Lisbon, Portugal"},{"name":"Faculty of Economics, University of Porto, R. 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