{"id":"https://openalex.org/W1967917458","doi":"https://doi.org/10.1109/cec.2010.5586116","title":"Finding a high coverage set of 5-biclusters with swarm intelligence","display_name":"Finding a high coverage set of 5-biclusters with swarm intelligence","publication_year":2010,"publication_date":"2010-07-01","ids":{"openalex":"https://openalex.org/W1967917458","doi":"https://doi.org/10.1109/cec.2010.5586116","mag":"1967917458"},"language":"en","primary_location":{"id":"doi:10.1109/cec.2010.5586116","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2010.5586116","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Congress on Evolutionary Computation","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010769668","display_name":"Fabr\u00edcio Olivetti de Fran\u00e7a","orcid":"https://orcid.org/0000-0002-2741-8736"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Fabricio O. de Franca","raw_affiliation_strings":["Laboratory of Bioinformatics and Bioinspired Computing, Department of Computer Engineering and Industrial Automation, School of Electrical and Computer Engineering, State University of Campinas-UNICAMP, Sao Paulo, Brazil","Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory of Bioinformatics and Bioinspired Computing, Department of Computer Engineering and Industrial Automation, School of Electrical and Computer Engineering, State University of Campinas-UNICAMP, Sao Paulo, Brazil","institution_ids":["https://openalex.org/I181391015"]},{"raw_affiliation_string":"Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil","institution_ids":["https://openalex.org/I181391015"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035858702","display_name":"Fernando J. Von Zuben","orcid":"https://orcid.org/0000-0002-4128-5415"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Fernando J. Von Zuben","raw_affiliation_strings":["Laboratory of Bioinformatics and Bioinspired Computing, Department of Computer Engineering and Industrial Automation, School of Electrical and Computer Engineering, State University of Campinas-UNICAMP, Sao Paulo, Brazil","Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory of Bioinformatics and Bioinspired Computing, Department of Computer Engineering and Industrial Automation, School of Electrical and Computer Engineering, State University of Campinas-UNICAMP, Sao Paulo, Brazil","institution_ids":["https://openalex.org/I181391015"]},{"raw_affiliation_string":"Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil","institution_ids":["https://openalex.org/I181391015"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181391015"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.998199999332428,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.998199999332428,"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":0.9980000257492065,"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"}},{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/biclustering","display_name":"Biclustering","score":0.7483295202255249},{"id":"https://openalex.org/keywords/row-and-column-spaces","display_name":"Row and column spaces","score":0.6221129894256592},{"id":"https://openalex.org/keywords/row","display_name":"Row","score":0.591098964214325},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5873399376869202},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5331097841262817},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.5181764364242554},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.49090510606765747},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.478415310382843},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4623395800590515},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40953439474105835},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3837428092956543},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2889537811279297},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.23393818736076355},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.16891101002693176}],"concepts":[{"id":"https://openalex.org/C144817290","wikidata":"https://www.wikidata.org/wiki/Q2976575","display_name":"Biclustering","level":5,"score":0.7483295202255249},{"id":"https://openalex.org/C104140500","wikidata":"https://www.wikidata.org/wiki/Q2088159","display_name":"Row and column spaces","level":3,"score":0.6221129894256592},{"id":"https://openalex.org/C135598885","wikidata":"https://www.wikidata.org/wiki/Q1366302","display_name":"Row","level":2,"score":0.591098964214325},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5873399376869202},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5331097841262817},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.5181764364242554},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.49090510606765747},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.478415310382843},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4623395800590515},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40953439474105835},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3837428092956543},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2889537811279297},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.23393818736076355},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.16891101002693176},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.0},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec.2010.5586116","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2010.5586116","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Congress on Evolutionary Computation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W83080091","https://openalex.org/W139609527","https://openalex.org/W1489772970","https://openalex.org/W1493217831","https://openalex.org/W1963591609","https://openalex.org/W1968091311","https://openalex.org/W1977496278","https://openalex.org/W2036328877","https://openalex.org/W2055849881","https://openalex.org/W2111203738","https://openalex.org/W2133576408","https://openalex.org/W2134023113","https://openalex.org/W2142460132","https://openalex.org/W2147246240","https://openalex.org/W2151758915","https://openalex.org/W2152066329","https://openalex.org/W2324108981","https://openalex.org/W4242399520","https://openalex.org/W6629329278"],"related_works":["https://openalex.org/W2313440505","https://openalex.org/W3123744736","https://openalex.org/W2137691148","https://openalex.org/W1505848319","https://openalex.org/W2152668278","https://openalex.org/W3084408672","https://openalex.org/W1979810043","https://openalex.org/W2397510698","https://openalex.org/W2506426934","https://openalex.org/W2611629964"],"abstract_inverted_index":{"Biclustering":[0],"is":[1,21,84,215,250],"usually":[2,144],"referred":[3],"to":[4,26,32,44,112,129,146,197,217],"as":[5,55,160],"the":[6,48,56,78,90,93,101,117,121,136,140,156,178,193,205,226,270],"process":[7],"of":[8,11,37,58,62,69,100,103,116,123,149,177,182,229,252,256],"finding":[9,59,253],"subsets":[10],"rows":[12],"and":[13,24,180,224,240,267],"columns":[14],"from":[15],"a":[16,22,27,34,60,66,73,86,98,113,147,161,164,199,210,241,254,263],"given":[17,120],"dataset.":[18],"Each":[19],"subset":[20],"bicluster":[23,79,141],"corresponds":[25],"sub-matrix":[28],"whose":[29],"elements":[30,105],"tend":[31],"present":[33],"high":[35,114,165,259,264],"degree":[36,68],"coherence":[38,271],"with":[39,225,258],"each":[40],"other.":[41],"In":[42,207],"order":[43,196],"find":[45,130,219],"such":[46,131],"structures,":[47],"\u03b4-biclustering":[49],"problem":[50,57],"was":[51],"formulated,":[52],"being":[53],"denoted":[54],"set":[61,148,255],"biclusters":[63,91,124,132,150,220,257],"limited":[64],"by":[65,72,107],"maximum":[67,231],"coherence,":[70],"measured":[71],"mean-squared":[74,137],"residue,":[75],"while":[76,261],"maximizing":[77],"total":[80],"size.":[81,142],"Additionally,":[82],"it":[83],"expected":[85],"reduced":[87],"overlap":[88,166],"among":[89,167],"in":[92,95,195],"set,":[94],"other":[96,185,245],"words,":[97],"minimization":[99],"number":[102,122],"common":[104],"shared":[106],"them.":[108,168],"This":[109,143,169],"also":[110,268],"leads":[111,145],"coverage":[115],"original":[118],"dataset":[119,179,194],"found.":[125],"Most":[126],"algorithms":[127],"intended":[128],"focus":[133],"only":[134],"on":[135,174,184],"residue":[138],"and/or":[139],"that":[151,248],"do":[152],"not":[153],"fully":[154],"cover":[155],"whole":[157],"data":[158],"and,":[159],"consequence,":[162],"shares":[163],"may":[170],"generate":[171],"redundant":[172],"information":[173,183],"some":[175,188],"portions":[176],"lack":[181],"portions.":[186],"Also,":[187],"methods":[189],"introduce":[190],"noise":[191,223],"into":[192],"promote":[198],"better":[200],"coverage,":[201,260],"but":[202],"sometimes":[203],"misleading":[204],"search.":[206],"this":[208],"paper,":[209],"swarm-based":[211],"approach,":[212],"named":[213],"SwarmBcluster,":[214],"created":[216],"effectively":[218],"without":[221],"introducing":[222],"main":[227],"objective":[228],"achieving":[230],"coverage.":[232],"Experiments":[233],"were":[234],"performed":[235],"considering":[236,244],"two":[237],"well-known":[238],"datasets":[239],"comparative":[242],"analysis":[243],"approaches":[246],"indicates":[247],"SwarmBcluster":[249],"capable":[251],"maintaining":[262],"average":[265],"volume":[266],"obeying":[269],"constraint":[272],"imposed.":[273]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}