{"id":"https://openalex.org/W3018603748","doi":"https://doi.org/10.1007/s41060-020-00216-2","title":"Clustering of mixed-type data considering concept hierarchies: problem specification and algorithm","display_name":"Clustering of mixed-type data considering concept hierarchies: problem specification and algorithm","publication_year":2020,"publication_date":"2020-04-25","ids":{"openalex":"https://openalex.org/W3018603748","doi":"https://doi.org/10.1007/s41060-020-00216-2","mag":"3018603748"},"language":"en","primary_location":{"id":"doi:10.1007/s41060-020-00216-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41060-020-00216-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41060-020-00216-2.pdf","source":{"id":"https://openalex.org/S4210195017","display_name":"International Journal of Data Science and Analytics","issn_l":"2364-415X","issn":["2364-415X","2364-4168"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Science and Analytics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s41060-020-00216-2.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011835178","display_name":"Sahar Behzadi","orcid":null},"institutions":[{"id":"https://openalex.org/I129774422","display_name":"University of Vienna","ror":"https://ror.org/03prydq77","country_code":"AT","type":"education","lineage":["https://openalex.org/I129774422"]}],"countries":["AT"],"is_corresponding":true,"raw_author_name":"Sahar Behzadi","raw_affiliation_strings":["Faculty of Computer Science, Data Mining, University of Vienna, Vienna, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science, Data Mining, University of Vienna, Vienna, Austria","institution_ids":["https://openalex.org/I129774422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010929895","display_name":"Nikola S. M\u00fcller","orcid":"https://orcid.org/0000-0001-8659-4548"},"institutions":[{"id":"https://openalex.org/I3018134672","display_name":"Helmholtz Zentrum M\u00fcnchen","ror":"https://ror.org/00cfam450","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I3018134672"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Nikola S. M\u00fcller","raw_affiliation_strings":["Helmholtz Research Center, Munich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Helmholtz Research Center, Munich, Germany","institution_ids":["https://openalex.org/I3018134672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009516958","display_name":"Claudia Plant","orcid":"https://orcid.org/0000-0001-5274-8123"},"institutions":[{"id":"https://openalex.org/I129774422","display_name":"University of Vienna","ror":"https://ror.org/03prydq77","country_code":"AT","type":"education","lineage":["https://openalex.org/I129774422"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Claudia Plant","raw_affiliation_strings":["Faculty of Computer Science, Data Mining, University of Vienna, Vienna, Austria","ds:Univie, Vienna, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science, Data Mining, University of Vienna, Vienna, Austria","institution_ids":["https://openalex.org/I129774422"]},{"raw_affiliation_string":"ds:Univie, Vienna, Austria","institution_ids":["https://openalex.org/I129774422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062860517","display_name":"Christian B\u00f6hm","orcid":"https://orcid.org/0000-0002-2237-9969"},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christian B\u00f6hm","raw_affiliation_strings":["University of Munich, Munich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Munich, Munich, Germany","institution_ids":["https://openalex.org/I8204097"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5011835178"],"corresponding_institution_ids":["https://openalex.org/I129774422"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":1.2241,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.83864448,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"10","issue":"3","first_page":"233","last_page":"248"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9994999766349792,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9980000257492065,"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/T11106","display_name":"Data Management and Algorithms","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/categorical-variable","display_name":"Categorical variable","score":0.8946732878684998},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6245035529136658},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6088005304336548},{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.5997436046600342},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5825026035308838},{"id":"https://openalex.org/keywords/data-type","display_name":"Data type","score":0.44296780228614807},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41737863421440125},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3450492322444916},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3053608536720276}],"concepts":[{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.8946732878684998},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6245035529136658},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6088005304336548},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.5997436046600342},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5825026035308838},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.44296780228614807},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41737863421440125},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3450492322444916},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3053608536720276},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s41060-020-00216-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41060-020-00216-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41060-020-00216-2.pdf","source":{"id":"https://openalex.org/S4210195017","display_name":"International Journal of Data Science and Analytics","issn_l":"2364-415X","issn":["2364-415X","2364-4168"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Science and Analytics","raw_type":"journal-article"},{"id":"pmh:oai:opus-zb.helmholtz-muenchen.de:59713","is_oa":true,"landing_page_url":"https://push-zb.helmholtz-muenchen.de/frontdoor.php?source_opus=59713","pdf_url":null,"source":{"id":"https://openalex.org/S4377196115","display_name":"Site cant be reached","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Int. J. Data Sci. Anal. 10, 233\u2013248 (2020)","raw_type":"Text"},{"id":"pmh:oai:push-zb.helmholtz-munich.de:59713","is_oa":true,"landing_page_url":"https://push-zb.helmholtz-munich.de/frontdoor.php?source_opus=59713","pdf_url":null,"source":{"id":"https://openalex.org/S7407055352","display_name":"PuSH - Publication Server of Helmholtz Zentrum M\u00fcnchen","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Int. J. Data Sci. Anal. 10, 233\u2013248 (2020)","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s41060-020-00216-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41060-020-00216-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41060-020-00216-2.pdf","source":{"id":"https://openalex.org/S4210195017","display_name":"International Journal of Data Science and Analytics","issn_l":"2364-415X","issn":["2364-415X","2364-4168"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Science and Analytics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321691","display_name":"Universit\u00e4t Wien","ror":"https://ror.org/03prydq77"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3018603748.pdf","grobid_xml":"https://content.openalex.org/works/W3018603748.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1560498978","https://openalex.org/W1608568320","https://openalex.org/W1988157641","https://openalex.org/W1990643970","https://openalex.org/W1990694217","https://openalex.org/W2076331049","https://openalex.org/W2081584164","https://openalex.org/W2106596127","https://openalex.org/W2109622481","https://openalex.org/W2113054345","https://openalex.org/W2121031611","https://openalex.org/W2149230623","https://openalex.org/W2198318593","https://openalex.org/W2224746910","https://openalex.org/W2579140808","https://openalex.org/W2788057792","https://openalex.org/W2886628535","https://openalex.org/W2927768435","https://openalex.org/W3120740533"],"related_works":["https://openalex.org/W4386799044","https://openalex.org/W2773208253","https://openalex.org/W2560646951","https://openalex.org/W4297454206","https://openalex.org/W65104662","https://openalex.org/W1871748041","https://openalex.org/W2362286668","https://openalex.org/W2133382151","https://openalex.org/W4245750691","https://openalex.org/W2378724343"],"abstract_inverted_index":{"Abstract":[0],"Most":[1],"clustering":[2],"algorithms":[3],"have":[4],"been":[5],"designed":[6],"only":[7],"for":[8],"pure":[9,12],"numerical":[10,59,143],"or":[11],"categorical":[13,55,82,88,141,165],"data":[14,102,173,200],"sets,":[15],"while":[16],"nowadays":[17],"many":[18],"applications":[19],"generate":[20],"mixed":[21],"data.":[22,166],"It":[23,45],"raises":[24],"the":[25,77,87,95,129,136,191],"question":[26],"how":[27],"to":[28],"integrate":[29],"various":[30,199],"types":[31],"of":[32,43,54,135,147,154,193],"attributes":[33,56,144],"so":[34],"that":[35,50,176],"one":[36],"could":[37],"efficiently":[38],"group":[39],"objects":[40],"without":[41],"loss":[42],"information.":[44],"is":[46,61,126,156,178],"already":[47],"well":[48,157,197],"understood":[49],"a":[51,58,70,148,185],"simple":[52],"conversion":[53],"into":[57,164],"domain":[60],"not":[62],"sufficient":[63],"since":[64,159],"relationships":[65],"between":[66],"values":[67],"such":[68],"as":[69,109,196,198],"certain":[71],"order":[72],"are":[73],"artificially":[74],"introduced.":[75],"Leveraging":[76],"natural":[78],"conceptual":[79,137],"hierarchy":[80],"among":[81],"information,":[83],"concept":[84,160,194],"trees":[85,161],"summarize":[86],"attributes.":[89],"In":[90],"this":[91,203],"paper,":[92],"we":[93,189],"introduce":[94],"algorithm":[96],"ClicoT":[97,139,155,177],"(":[98],"CL":[99],"ustering":[100],"mixed-type":[101],"I":[103],"ncluding":[104],"CO":[105],"ncept":[106],"T":[107],"rees)":[108],"reported":[110],"by":[111,145],"Behzadi":[112],"et":[113],"al.":[114],"(Advances":[115],"in":[116,184,202],"Knowledge":[117],"Discovery":[118],"and":[119,142,171,180],"Data":[120],"Mining,":[121],"Springer,":[122],"Cham,":[123],"2019)":[124],"which":[125],"based":[127],"on":[128,169],"minimum":[130],"description":[131],"length":[132],"principle.":[133],"Profiting":[134],"hierarchies,":[138],"integrates":[140],"means":[146],"MDL-based":[149],"objective":[150],"function.":[151],"The":[152],"result":[153],"interpretable":[158],"provide":[162],"insights":[163],"Extensive":[167],"experiments":[168],"synthetic":[170],"real":[172],"sets":[174],"illustrate":[175],"noise-robust":[179],"yields":[181],"well-interpretable":[182],"results":[183],"short":[186],"runtime.":[187],"Moreover,":[188],"investigate":[190],"impact":[192],"hierarchies":[195],"characteristics":[201],"paper.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}