{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T02:42:06Z","timestamp":1790995326271,"version":"4.1.0"},"reference-count":39,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2024,10,20]],"date-time":"2024-10-20T00:00:00Z","timestamp":1729382400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Health","award":["CUP D93C22000640001"],"award-info":[{"award-number":["CUP D93C22000640001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>Clustering is a very common means of analysis of the data present in large datasets, with the aims of understanding and summarizing the data and discovering similarities, among other goals. However, despite the present success of the use of subsymbolic methods for data clustering, a description of the obtained clusters cannot rely on the intricacies of the subsymbolic processing. For clusters of data expressed in a Resource Description Framework (RDF), we extend and implement an optimized, previously proposed, logic-based methodology that computes an RDF structure\u2014called a Common Subsumer\u2014describing the commonalities among all resources. We tested our implementation with two open, and very different, RDF datasets: one devoted to public procurement, and the other devoted to drugs in pharmacology. For both datasets, we were able to provide reasonably concise and readable descriptions of clusters with up to 1800 resources. Our analysis shows the viability of our methodology and computation, and paves the way for general cluster explanations to be provided to lay users.<\/jats:p>","DOI":"10.3390\/data9100121","type":"journal-article","created":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T03:57:09Z","timestamp":1729483029000},"page":"121","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Computing the Commonalities of Clusters in Resource Description Framework: Computational Aspects"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8774-4816","authenticated-orcid":false,"given":"Simona","family":"Colucci","sequence":"first","affiliation":[{"name":"Dipartimento di Ingegneria Elettrica e dell\u2019Informazione (DEI), Politecnico di Bari, Via Orabona 4, 70125 Bari, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0284-9625","authenticated-orcid":false,"given":"Francesco Maria","family":"Donini","sequence":"additional","affiliation":[{"name":"Dipartimento di Scienze Umanistiche, della Comunicazione e del Turismo (DISUCOM), Universit\u00e0 della Tuscia, Via Santa Maria in Gradi, 4, 01100 Viterbo, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5484-9945","authenticated-orcid":false,"given":"Eugenio","family":"Di Sciascio","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Elettrica e dell\u2019Informazione (DEI), Politecnico di Bari, Via Orabona 4, 70125 Bari, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,20]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"A Survey and an Empirical Evaluation of Multi-View Clustering Approaches","volume":"56","author":"Zhou","year":"2024","journal-title":"ACM Comput. 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