{"id":"https://openalex.org/W1994258566","doi":"https://doi.org/10.1109/cec.2014.6900586","title":"Multi-view clustering of web documents using multi-objective genetic algorithm","display_name":"Multi-view clustering of web documents using multi-objective genetic algorithm","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W1994258566","doi":"https://doi.org/10.1109/cec.2014.6900586","mag":"1994258566"},"language":"en","primary_location":{"id":"doi:10.1109/cec.2014.6900586","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2014.6900586","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 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":22,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2625","last_page":"2632"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9972000122070312,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9972000122070312,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.996399998664856,"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":0.9940999746322632,"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":0.9231948852539062},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.7606377601623535},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.724503755569458},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.7206031084060669},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7043383121490479},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6093811392784119},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.5272342562675476},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.51936274766922},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.5090660452842712},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.4685826003551483},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4462594985961914},{"id":"https://openalex.org/keywords/single-linkage-clustering","display_name":"Single-linkage clustering","score":0.4207618236541748},{"id":"https://openalex.org/keywords/constrained-clustering","display_name":"Constrained clustering","score":0.41897523403167725},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3554110527038574},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32463592290878296},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2782658040523529}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.9231948852539062},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.7606377601623535},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.724503755569458},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.7206031084060669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7043383121490479},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6093811392784119},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.5272342562675476},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.51936274766922},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.5090660452842712},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.4685826003551483},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4462594985961914},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.4207618236541748},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.41897523403167725},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3554110527038574},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32463592290878296},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2782658040523529},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec.2014.6900586","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2014.6900586","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 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":47,"referenced_works":["https://openalex.org/W18428236","https://openalex.org/W35043963","https://openalex.org/W100104462","https://openalex.org/W1480428252","https://openalex.org/W1481462362","https://openalex.org/W1536496053","https://openalex.org/W1553373771","https://openalex.org/W1560265110","https://openalex.org/W1585939719","https://openalex.org/W1608127741","https://openalex.org/W1792069146","https://openalex.org/W1861576520","https://openalex.org/W1890896919","https://openalex.org/W1940737455","https://openalex.org/W1965059951","https://openalex.org/W1974758710","https://openalex.org/W1992419399","https://openalex.org/W1996747841","https://openalex.org/W2011430131","https://openalex.org/W2025395689","https://openalex.org/W2031046392","https://openalex.org/W2034662733","https://openalex.org/W2086808754","https://openalex.org/W2097645701","https://openalex.org/W2103781895","https://openalex.org/W2105068202","https://openalex.org/W2108031918","https://openalex.org/W2108502868","https://openalex.org/W2115346774","https://openalex.org/W2119137875","https://openalex.org/W2120529703","https://openalex.org/W2126105956","https://openalex.org/W2130851950","https://openalex.org/W2131435419","https://openalex.org/W2136480620","https://openalex.org/W2138745909","https://openalex.org/W2151153628","https://openalex.org/W2162934302","https://openalex.org/W2166143448","https://openalex.org/W2210195496","https://openalex.org/W4235169531","https://openalex.org/W4252059084","https://openalex.org/W4285719527","https://openalex.org/W4300631968","https://openalex.org/W6633397205","https://openalex.org/W6639027437","https://openalex.org/W6657882739"],"related_works":["https://openalex.org/W2160785859","https://openalex.org/W3168768270","https://openalex.org/W3140018618","https://openalex.org/W2559422900","https://openalex.org/W2025839902","https://openalex.org/W2163563073","https://openalex.org/W1491908038","https://openalex.org/W2970954390","https://openalex.org/W2149742493","https://openalex.org/W2626264717"],"abstract_inverted_index":{"Clustering":[0],"ensembles":[1],"are":[2,22],"a":[3,11,16,72,84,91,107,113,129],"common":[4],"approach":[5,35,54],"to":[6,24,31,99,111],"clustering":[7,14,39,63,79,86,93,102,115],"problem,":[8],"which":[9,81,127],"combine":[10,32],"collection":[12],"of":[13,45,55,74,109],"into":[15],"superior":[17],"solution.":[18,87,116],"The":[19,150],"key":[20],"issues":[21],"how":[23,30],"generate":[25,100],"different":[26,77,101],"candidate":[27,38,62,78],"solutions":[28,40,64,80,103],"and":[29,51,104],"them.":[33],"Common":[34],"for":[36],"generating":[37],"ignores":[41,65],"the":[42,46,52,58,66],"multiple":[43,49,97],"representations":[44],"data":[47,144],"(i.e.,":[48],"views)":[50],"standard":[53],"simply":[56],"selecting":[57],"best":[59],"solution":[60],"from":[61,76],"fact":[67],"that":[68,95,146,153],"there":[69],"may":[70],"be":[71],"set":[73],"clusters":[75,110],"can":[82],"form":[83,112],"better":[85],"This":[88],"paper":[89],"presents":[90],"new":[92,134],"method":[94,118,135,155],"exploits":[96],"views":[98],"then":[105],"selects":[106],"combination":[108],"final":[114],"Our":[117,133],"is":[119,128,136],"based":[120],"on":[121,142],"Nondominated":[122],"Sorting":[123],"Genetic":[124],"Algorithm":[125],"(NSGA-II),":[126],"multi-objective":[130],"optimization":[131],"approach.":[132],"compared":[137],"with":[138],"five":[139],"existing":[140],"algorithms":[141],"three":[143],"sets":[145],"have":[147],"increasing":[148],"difficulty.":[149],"results":[151],"show":[152],"our":[154],"significantly":[156],"outperforms":[157],"other":[158],"methods.":[159]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}