{"id":"https://openalex.org/W3169881201","doi":"https://doi.org/10.1007/s11634-022-00510-w","title":"Band depth based initialization of K-means for functional data clustering","display_name":"Band depth based initialization of K-means for functional data clustering","publication_year":2022,"publication_date":"2022-09-03","ids":{"openalex":"https://openalex.org/W3169881201","doi":"https://doi.org/10.1007/s11634-022-00510-w","mag":"3169881201"},"language":"en","primary_location":{"id":"doi:10.1007/s11634-022-00510-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11634-022-00510-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11634-022-00510-w.pdf","source":{"id":"https://openalex.org/S4210175730","display_name":"Advances in Data Analysis and Classification","issn_l":"1862-5347","issn":["1862-5347","1862-5355"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","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":"Advances in Data Analysis and Classification","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/s11634-022-00510-w.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068033678","display_name":"Javier Albert-Smet","orcid":null},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Javier Albert-Smet","raw_affiliation_strings":["Departamento de Estad\u00edstica, Universidad Carlos III de Madrid, C/ Madrid 126, Getafe, 28903, Madrid, Spain","Departamento de Estad\u00edstica, Universidad Carlos III de Madrid, Getafe, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departamento de Estad\u00edstica, Universidad Carlos III de Madrid, C/ Madrid 126, Getafe, 28903, Madrid, Spain","institution_ids":["https://openalex.org/I50357001"]},{"raw_affiliation_string":"Departamento de Estad\u00edstica, Universidad Carlos III de Madrid, Getafe, Spain","institution_ids":["https://openalex.org/I50357001"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059403765","display_name":"Aurora Torrente","orcid":"https://orcid.org/0000-0001-9183-8367"},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Aurora Torrente","raw_affiliation_strings":["Departamento de Matem\u00e1ticas, Instituto Gregorio Mill\u00e1n, Universidad Carlos III de Madrid, Av. Universidad 30, Legan\u00e9s, 28911, Madrid, Spain","Departamento de Matem\u00e1ticas, Instituto Gregorio Mill\u00e1n, Universidad Carlos III de Madrid, Legan\u00e9s, Spain"],"raw_orcid":"https://orcid.org/0000-0001-9183-8367","affiliations":[{"raw_affiliation_string":"Departamento de Matem\u00e1ticas, Instituto Gregorio Mill\u00e1n, Universidad Carlos III de Madrid, Av. Universidad 30, Legan\u00e9s, 28911, Madrid, Spain","institution_ids":["https://openalex.org/I50357001"]},{"raw_affiliation_string":"Departamento de Matem\u00e1ticas, Instituto Gregorio Mill\u00e1n, Universidad Carlos III de Madrid, Legan\u00e9s, Spain","institution_ids":["https://openalex.org/I50357001"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025167015","display_name":"Juan Romo","orcid":"https://orcid.org/0000-0002-0789-089X"},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Juan Romo","raw_affiliation_strings":["Departamento de Estad\u00edstica, Universidad Carlos III de Madrid, C/ Madrid 126, Getafe, 28903, Madrid, Spain","Departamento de Estad\u00edstica, Universidad Carlos III de Madrid, Getafe, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departamento de Estad\u00edstica, Universidad Carlos III de Madrid, C/ Madrid 126, Getafe, 28903, Madrid, Spain","institution_ids":["https://openalex.org/I50357001"]},{"raw_affiliation_string":"Departamento de Estad\u00edstica, Universidad Carlos III de Madrid, Getafe, Spain","institution_ids":["https://openalex.org/I50357001"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5059403765"],"corresponding_institution_ids":["https://openalex.org/I50357001"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.5549,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.7048388,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"17","issue":"2","first_page":"463","last_page":"484"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9952999949455261,"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":0.9952999949455261,"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/T11106","display_name":"Data Management and Algorithms","score":0.9843000173568726,"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"}},{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9750999808311462,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8258044123649597},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.8168332576751709},{"id":"https://openalex.org/keywords/resampling","display_name":"Resampling","score":0.6025915741920471},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5865628719329834},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5618208646774292},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.556394636631012},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5259040594100952},{"id":"https://openalex.org/keywords/centroid","display_name":"Centroid","score":0.4997239112854004},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.49811601638793945},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.41736355423927307},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3665379285812378},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35698938369750977},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3338821530342102},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29881638288497925}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8258044123649597},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.8168332576751709},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.6025915741920471},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5865628719329834},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5618208646774292},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.556394636631012},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5259040594100952},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.4997239112854004},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.49811601638793945},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.41736355423927307},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3665379285812378},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35698938369750977},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3338821530342102},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29881638288497925},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s11634-022-00510-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11634-022-00510-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11634-022-00510-w.pdf","source":{"id":"https://openalex.org/S4210175730","display_name":"Advances in Data Analysis and Classification","issn_l":"1862-5347","issn":["1862-5347","1862-5355"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","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":"Advances in Data Analysis and Classification","raw_type":"journal-article"},{"id":"pmh:oai:e-archivo.uc3m.es:10016/37332","is_oa":true,"landing_page_url":"http://hdl.handle.net/10016/37332","pdf_url":"https://e-archivo.uc3m.es/bitstreams/fb1c1243-421a-473f-bd72-1a29aa5da418/download","source":{"id":"https://openalex.org/S4306400817","display_name":"e-Archivo (Carlos III University of Madrid)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I50357001","host_organization_name":"Universidad Carlos III de Madrid","host_organization_lineage":["https://openalex.org/I50357001"],"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":"","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:RePEc:spr:advdac:v:17:y:2023:i:2:d:10.1007_s11634-022-00510-w","is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s11634-022-00510-w","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s11634-022-00510-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11634-022-00510-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11634-022-00510-w.pdf","source":{"id":"https://openalex.org/S4210175730","display_name":"Advances in Data Analysis and Classification","issn_l":"1862-5347","issn":["1862-5347","1862-5355"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","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":"Advances in Data Analysis and Classification","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6302844841","display_name":null,"funder_award_id":"PID2020-112796RB-C22","funder_id":"https://openalex.org/F4320315062","funder_display_name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades"},{"id":"https://openalex.org/G6731524417","display_name":null,"funder_award_id":"PID2020","funder_id":"https://openalex.org/F4320315062","funder_display_name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades"}],"funders":[{"id":"https://openalex.org/F4320315062","display_name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3169881201.pdf","grobid_xml":"https://content.openalex.org/works/W3169881201.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W611353362","https://openalex.org/W1489608363","https://openalex.org/W1493454437","https://openalex.org/W1513893380","https://openalex.org/W1579694346","https://openalex.org/W1966951118","https://openalex.org/W1983908352","https://openalex.org/W1991308917","https://openalex.org/W2002586964","https://openalex.org/W2011039300","https://openalex.org/W2016381774","https://openalex.org/W2029069446","https://openalex.org/W2045649740","https://openalex.org/W2047046780","https://openalex.org/W2059515884","https://openalex.org/W2060207914","https://openalex.org/W2073459066","https://openalex.org/W2073849744","https://openalex.org/W2085570173","https://openalex.org/W2101108516","https://openalex.org/W2111953658","https://openalex.org/W2126804335","https://openalex.org/W2127170577","https://openalex.org/W2138447378","https://openalex.org/W2150097763","https://openalex.org/W2163352133","https://openalex.org/W2887386157","https://openalex.org/W2894798061","https://openalex.org/W2999729612","https://openalex.org/W3021971632","https://openalex.org/W3045268955","https://openalex.org/W4235169531","https://openalex.org/W4240093485","https://openalex.org/W4250766106"],"related_works":["https://openalex.org/W3204184292","https://openalex.org/W3176564347","https://openalex.org/W1985458517","https://openalex.org/W2355833770","https://openalex.org/W3031039437","https://openalex.org/W3095877357","https://openalex.org/W183202219","https://openalex.org/W4387877362","https://openalex.org/W4385595302","https://openalex.org/W3216119459"],"abstract_inverted_index":{"Abstract":[0],"The":[1],"k":[2,40,196],"-Means":[3,197],"algorithm":[4],"is":[5,16,26,46],"one":[6,58],"of":[7,30,44,57,59,71,77,84,138,148,180,200],"the":[8,22,62,78,82,85,95,142,145,149,168,181],"most":[9],"popular":[10],"choices":[11],"for":[12,39,132],"clustering":[13,68,201],"data":[14,56,79,157],"but":[15],"well-known":[17],"to":[18,21,54,107,167,194],"be":[19],"sensitive":[20],"initialization":[23],"process.":[24],"There":[25],"a":[27,69,100,111],"substantial":[28],"number":[29],"methods":[31],"that":[32,65,114,160],"aim":[33],"at":[34,191],"finding":[35],"optimal":[36],"initial":[37,135],"seeds":[38,193],"-Means,":[41],"though":[42],"none":[43],"them":[45,139],"universally":[47],"valid.":[48],"This":[49],"paper":[50],"presents":[51],"an":[52],"extension":[53],"longitudinal":[55],"such":[60,121],"methods,":[61],"BRIk":[63,96],"algorithm,":[64],"relies":[66],"on":[67,81],"set":[70],"centroids":[72],"derived":[73,129],"from":[74],"bootstrap":[75],"replicates":[76],"and":[80,110,118,155,172],"use":[83],"versatile":[86],"Modified":[87],"Band":[88],"Depth.":[89],"In":[90],"our":[91,108,161,173],"approach":[92],"we":[93,103],"improve":[94],"method":[97,170,183],"by":[98],"adding":[99],"step":[101],"where":[102],"fit":[104],"appropriate":[105],"B-splines":[106],"observations":[109],"resampling":[112],"process":[113],"allows":[115],"computational":[116],"feasibility":[117],"handling":[119],"issues":[120],"as":[122],"noise":[123],"or":[124,144],"missing":[125],"data.":[126,150],"We":[127],"have":[128],"two":[130],"techniques":[131],"providing":[133,192],"suitable":[134],"seeds,":[136],"each":[137],"stressing":[140],"respectively":[141],"multivariate":[143],"functional":[146],"nature":[147],"Our":[151],"results":[152],"with":[153],"simulated":[154],"real":[156],"sets":[158],"indicate":[159],"F":[162,174],"unctional":[163,175],"Data":[164],"A":[165],"pproach":[166],"BRIK":[169,182],"(FABRIk)":[171],"D":[176],"ata":[177],"E":[178],"xtension":[179],"(FDEBRIk)":[184],"are":[185],"more":[186],"effective":[187],"than":[188],"previous":[189],"proposals":[190],"initialize":[195],"in":[198],"terms":[199],"recovery.":[202]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
