{"id":"https://openalex.org/W4385437883","doi":"https://doi.org/10.24963/kr.2023/58","title":"Explainable Clustering with CREAM","display_name":"Explainable Clustering with CREAM","publication_year":2023,"publication_date":"2023-07-31","ids":{"openalex":"https://openalex.org/W4385437883","doi":"https://doi.org/10.24963/kr.2023/58"},"language":"en","primary_location":{"id":"doi:10.24963/kr.2023/58","is_oa":true,"landing_page_url":"https://doi.org/10.24963/kr.2023/58","pdf_url":"https://proceedings.kr.org/2023/58/kr2023-0058-sabbatini-et-al.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twentieth International Conference on Principles of Knowledge Representation and Reasoning","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://proceedings.kr.org/2023/58/kr2023-0058-sabbatini-et-al.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065564015","display_name":"Federico Sabbatini","orcid":"https://orcid.org/0000-0002-0532-6777"},"institutions":[{"id":"https://openalex.org/I190397597","display_name":"University of Urbino","ror":"https://ror.org/04q4kt073","country_code":"IT","type":"education","lineage":["https://openalex.org/I190397597"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Federico Sabbatini","raw_affiliation_strings":["University of Urbino"],"affiliations":[{"raw_affiliation_string":"University of Urbino","institution_ids":["https://openalex.org/I190397597"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090610404","display_name":"Roberta Calegari","orcid":"https://orcid.org/0000-0003-3794-2942"},"institutions":[{"id":"https://openalex.org/I9360294","display_name":"University of Bologna","ror":"https://ror.org/01111rn36","country_code":"IT","type":"education","lineage":["https://openalex.org/I9360294"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Roberta Calegari","raw_affiliation_strings":["University of Bologna"],"affiliations":[{"raw_affiliation_string":"University of Bologna","institution_ids":["https://openalex.org/I9360294"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5065564015"],"corresponding_institution_ids":["https://openalex.org/I190397597"],"apc_list":null,"apc_paid":null,"fwci":2.0145,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.88626027,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"593","last_page":"603"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8277935981750488},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6569783687591553},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6026493310928345},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5963509678840637},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5487674474716187},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5384191870689392},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4794115722179413},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4326305091381073},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4269407391548157},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2885626554489136},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14859893918037415}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8277935981750488},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6569783687591553},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6026493310928345},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5963509678840637},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5487674474716187},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5384191870689392},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4794115722179413},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4326305091381073},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4269407391548157},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2885626554489136},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14859893918037415},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.24963/kr.2023/58","is_oa":true,"landing_page_url":"https://doi.org/10.24963/kr.2023/58","pdf_url":"https://proceedings.kr.org/2023/58/kr2023-0058-sabbatini-et-al.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twentieth International Conference on Principles of Knowledge Representation and Reasoning","raw_type":"proceedings-article"},{"id":"pmh:oai:cris.unibo.it:11585/952610","is_oa":true,"landing_page_url":"https://hdl.handle.net/11585/952610","pdf_url":"https://cris.unibo.it/bitstream/11585/952610/1/kr2023-0058-sabbatini-et-al.pdf","source":{"id":"https://openalex.org/S4306402579","display_name":"Archivio istituzionale della ricerca (Alma Mater Studiorum Universit\u00e0 di Bologna)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210117483","host_organization_name":"Istituto di Ematologia di Bologna","host_organization_lineage":["https://openalex.org/I4210117483"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"doi:10.24963/kr.2023/58","is_oa":true,"landing_page_url":"https://doi.org/10.24963/kr.2023/58","pdf_url":"https://proceedings.kr.org/2023/58/kr2023-0058-sabbatini-et-al.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twentieth International Conference on Principles of Knowledge Representation and Reasoning","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385437883.pdf"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W1503398984","https://openalex.org/W1673310716","https://openalex.org/W1980486587","https://openalex.org/W2001619934","https://openalex.org/W2022686119","https://openalex.org/W2030644393","https://openalex.org/W2061025330","https://openalex.org/W2064769840","https://openalex.org/W2070932809","https://openalex.org/W2101234009","https://openalex.org/W2106067233","https://openalex.org/W2121947440","https://openalex.org/W2135674549","https://openalex.org/W2138615112","https://openalex.org/W2150593711","https://openalex.org/W2162833336","https://openalex.org/W2310245665","https://openalex.org/W2527802371","https://openalex.org/W2583419234","https://openalex.org/W2899435277","https://openalex.org/W2902433822","https://openalex.org/W2969673498","https://openalex.org/W3034838735","https://openalex.org/W3184161979","https://openalex.org/W3204048750","https://openalex.org/W4226524988","https://openalex.org/W4251348903","https://openalex.org/W4297897402","https://openalex.org/W4323903890","https://openalex.org/W6630177651","https://openalex.org/W6650842192","https://openalex.org/W6656319447","https://openalex.org/W6668322514","https://openalex.org/W6675354045","https://openalex.org/W6677945368","https://openalex.org/W6682243771","https://openalex.org/W6756337444","https://openalex.org/W6774582773","https://openalex.org/W6810169507","https://openalex.org/W6817126606"],"related_works":["https://openalex.org/W4298130764","https://openalex.org/W2804364458","https://openalex.org/W2132641928","https://openalex.org/W4310225030","https://openalex.org/W2090259340","https://openalex.org/W1926736923","https://openalex.org/W2158836806","https://openalex.org/W4384470695","https://openalex.org/W3134840015","https://openalex.org/W4366979180"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"CREAM,":[3],"a":[4],"new":[5],"explainable":[6],"clustering":[7],"technique":[8],"based":[9],"on":[10],"decision":[11],"tree":[12],"induction,":[13],"providing":[14],"human-interpretable":[15],"clusters":[16],"by":[17],"performing":[18],"hypercubic":[19],"approximations":[20],"of":[21,67],"the":[22,41,59,65],"input":[23,45],"feature":[24],"space.":[25],"CREAM":[26,61,68],"may":[27],"also":[28,50],"be":[29],"applied":[30],"to":[31,57],"data":[32],"sets":[33],"describing":[34],"classification":[35],"and":[36,46,72],"regression":[37,73],"tasks,":[38],"given":[39],"that":[40],"algorithm":[42],"discriminates":[43],"amongst":[44],"output":[47],"features.":[48],"We":[49],"present":[51],"OrCHiD,":[52],"an":[53],"automated":[54],"tuning":[55],"procedure":[56],"select":[58],"optimum":[60],"parameter.":[62],"Experiments":[63],"demonstrating":[64],"effectiveness":[66],"in":[69,78],"clustering,":[70],"classification,":[71],"tasks":[74],"are":[75],"reported":[76],"here,":[77],"comparison":[79],"with":[80],"other":[81],"state-of-the-art":[82],"techniques":[83],"used":[84],"as":[85],"benchmarks.":[86]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":7}],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}
