{"id":"https://openalex.org/W1527057222","doi":"https://doi.org/10.1109/cec.2015.7257091","title":"Multi-objective multi-view clustering ensemble based on evolutionary approach","display_name":"Multi-objective multi-view clustering ensemble based on evolutionary approach","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W1527057222","doi":"https://doi.org/10.1109/cec.2015.7257091","mag":"1527057222"},"language":"en","primary_location":{"id":"doi:10.1109/cec.2015.7257091","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2015.7257091","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Congress on Evolutionary Computation (CEC)","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/A5045832324","display_name":"Abdul Wahid","orcid":"https://orcid.org/0000-0003-2835-6853"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Abdul Wahid","raw_affiliation_strings":["Victoria University of Wellington, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Victoria University of Wellington, New Zealand","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068382420","display_name":"Xiaoying Gao","orcid":"https://orcid.org/0000-0002-6326-7947"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Xiaoying Gao","raw_affiliation_strings":["Victoria University of Wellington, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Victoria University of Wellington, New Zealand","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043334999","display_name":"Peter Andreae","orcid":"https://orcid.org/0000-0002-2789-680X"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Peter Andreae","raw_affiliation_strings":["Victoria University of Wellington, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Victoria University of Wellington, New Zealand","institution_ids":["https://openalex.org/I41156924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I41156924"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9987000226974487,"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":0.9987000226974487,"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/T10100","display_name":"Metaheuristic Optimization 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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9746000170707703,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.9008944034576416},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.674828827381134},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.6519184112548828},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.6384025812149048},{"id":"https://openalex.org/keywords/crossover","display_name":"Crossover","score":0.6141504049301147},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.5755754113197327},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.52810138463974},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.4970989525318146},{"id":"https://openalex.org/keywords/constrained-clustering","display_name":"Constrained clustering","score":0.4624713957309723},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.4598707854747772},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.4544622302055359},{"id":"https://openalex.org/keywords/single-linkage-clustering","display_name":"Single-linkage clustering","score":0.4513952434062958},{"id":"https://openalex.org/keywords/consensus-clustering","display_name":"Consensus clustering","score":0.4344444274902344},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3335551619529724}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.9008944034576416},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.674828827381134},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.6519184112548828},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.6384025812149048},{"id":"https://openalex.org/C122507166","wikidata":"https://www.wikidata.org/wiki/Q628906","display_name":"Crossover","level":2,"score":0.6141504049301147},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.5755754113197327},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.52810138463974},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.4970989525318146},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.4624713957309723},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.4598707854747772},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.4544622302055359},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.4513952434062958},{"id":"https://openalex.org/C186767784","wikidata":"https://www.wikidata.org/wiki/Q5162841","display_name":"Consensus clustering","level":5,"score":0.4344444274902344},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3335551619529724}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec.2015.7257091","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2015.7257091","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W18428236","https://openalex.org/W1481462362","https://openalex.org/W1484287363","https://openalex.org/W1792069146","https://openalex.org/W1890896919","https://openalex.org/W1940737455","https://openalex.org/W1994258566","https://openalex.org/W1996747841","https://openalex.org/W2002767255","https://openalex.org/W2025395689","https://openalex.org/W2076408892","https://openalex.org/W2108031918","https://openalex.org/W2108502868","https://openalex.org/W2119137875","https://openalex.org/W2120529703","https://openalex.org/W2125295348","https://openalex.org/W2126105956","https://openalex.org/W2131435419","https://openalex.org/W2162934302","https://openalex.org/W2166143448","https://openalex.org/W2294414050","https://openalex.org/W4235169531","https://openalex.org/W4252684946"],"related_works":["https://openalex.org/W2188840951","https://openalex.org/W2160785859","https://openalex.org/W2199594781","https://openalex.org/W2590117803","https://openalex.org/W3186815950","https://openalex.org/W2202413591","https://openalex.org/W3124860551","https://openalex.org/W2038937869","https://openalex.org/W2965089876","https://openalex.org/W2309230723"],"abstract_inverted_index":{"Clustering":[0,19],"ensembles":[1,47,157],"is":[2,114],"a":[3,8,13,39,62,74,92,99,120],"clustering":[4,10,17,41,46,94,122,156],"technique":[5],"which":[6,125],"derives":[7],"better":[9],"solution":[11],"from":[12,34],"set":[14],"of":[15,91,98,139],"candidate":[16,32,93],"solutions.":[18],"ensemble":[20,123],"methods":[21,154],"have":[22],"to":[23,56,67,78,87,104],"address":[24,57,68],"two":[25,135],"distinct":[26],"but":[27],"interlinked":[28],"problems:":[29],"Generating":[30],"multiple":[31,54],"solutions":[33],"the":[35,58,69,80,89],"data":[36],"and":[37,61,83,107,134],"producing":[38],"final":[40],"solution.":[42,95],"Our":[43],"recently":[44],"proposed":[45],"method":[48,77,102,151],"(MMOEA)":[49],"based":[50],"on":[51,158],"NSGA-II":[52,112],"used":[53,73],"views":[55],"first":[59],"problem":[60],"novel":[63],"cluster":[64],"oriented":[65],"approach":[66],"second":[70],"problem.":[71],"MMOEA":[72],"simple":[75,100],"crossover":[76,101],"explore":[79],"search":[81],"space":[82],"three":[84,109],"objective":[85,136],"functions":[86,137],"determine":[88],"quality":[90],"The":[96,145],"use":[97],"led":[103],"slow":[105],"convergence":[106],"using":[108],"objectives":[110],"in":[111,141],"framework":[113],"often":[115],"discouraged.":[116],"This":[117],"paper":[118],"presents":[119],"new":[121,127,150],"method,":[124],"introduces":[126],"ideas":[128],"for":[129,155],"crossover,":[130],"mutation,":[131],"tuning":[132],"steps":[133],"(instead":[138],"three)":[140],"an":[142],"evolutionary":[143],"process.":[144],"results":[146],"show":[147],"that":[148],"our":[149],"outperforms":[152],"recent":[153],"different":[159],"multi-view":[160],"datasets.":[161]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}