{"id":"https://openalex.org/W2182707490","doi":"https://doi.org/10.1109/dsaa.2015.7344795","title":"Multi-objective clustering ensemble for high-dimensional data based on Strength Pareto Evolutionary Algorithm (SPEA-II)","display_name":"Multi-objective clustering ensemble for high-dimensional data based on Strength Pareto Evolutionary Algorithm (SPEA-II)","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2182707490","doi":"https://doi.org/10.1109/dsaa.2015.7344795","mag":"2182707490"},"language":"en","primary_location":{"id":"doi:10.1109/dsaa.2015.7344795","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa.2015.7344795","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA)","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":25,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","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/T10637","display_name":"Advanced Clustering Algorithms Research","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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9976999759674072,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9919999837875366,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8872190117835999},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7045717835426331},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.6157674789428711},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.5859595537185669},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.5562708377838135},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5478229522705078},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.5229240655899048},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.5053151249885559},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.5027763843536377},{"id":"https://openalex.org/keywords/consensus-clustering","display_name":"Consensus clustering","score":0.5025107860565186},{"id":"https://openalex.org/keywords/constrained-clustering","display_name":"Constrained clustering","score":0.48638632893562317},{"id":"https://openalex.org/keywords/document-clustering","display_name":"Document clustering","score":0.4747070372104645},{"id":"https://openalex.org/keywords/single-linkage-clustering","display_name":"Single-linkage clustering","score":0.42735564708709717},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4230967164039612},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3366404175758362}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8872190117835999},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7045717835426331},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.6157674789428711},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.5859595537185669},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.5562708377838135},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5478229522705078},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.5229240655899048},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.5053151249885559},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.5027763843536377},{"id":"https://openalex.org/C186767784","wikidata":"https://www.wikidata.org/wiki/Q5162841","display_name":"Consensus clustering","level":5,"score":0.5025107860565186},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.48638632893562317},{"id":"https://openalex.org/C177937566","wikidata":"https://www.wikidata.org/wiki/Q4223102","display_name":"Document clustering","level":3,"score":0.4747070372104645},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.42735564708709717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4230967164039612},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3366404175758362}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dsaa.2015.7344795","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa.2015.7344795","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA)","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":27,"referenced_works":["https://openalex.org/W18428236","https://openalex.org/W40976687","https://openalex.org/W1481462362","https://openalex.org/W1527057222","https://openalex.org/W1585939719","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/W2031046392","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/W2131435419","https://openalex.org/W2151153628","https://openalex.org/W2162934302","https://openalex.org/W2294414050","https://openalex.org/W4235169531","https://openalex.org/W4252684946","https://openalex.org/W4285719527","https://openalex.org/W6635097213","https://openalex.org/W6657882739"],"related_works":["https://openalex.org/W2199594781","https://openalex.org/W2130194910","https://openalex.org/W2187382873","https://openalex.org/W1577058187","https://openalex.org/W2533990316","https://openalex.org/W2620179200","https://openalex.org/W2071000654","https://openalex.org/W2594747375","https://openalex.org/W2727104601","https://openalex.org/W2965089876"],"abstract_inverted_index":{"Clustering":[0,45],"is":[1,76,107,166,226],"one":[2,116],"of":[3,15,72,91,161,172,207,231],"the":[4,56,73,77,92,104,109,158,162,173,197,204,217,228,236],"fundamental":[5],"data":[6,57,138],"analysis":[7],"techniques,":[8],"which":[9,215],"aims":[10],"to":[11,31,135,168,202,234],"find":[12],"distinct":[13],"groups":[14],"similar":[16],"objects":[17],"and":[18,58,164],"discovers":[19],"hidden":[20],"structures":[21],"in":[22,227],"data.":[23],"A":[24,70,125],"recent":[25],"clustering":[26,28,35,43,53,62,68,117,123,127,184,208,219,251],"approach,":[27],"ensembles":[29,46],"tries":[30],"derive":[32],"an":[33],"improved":[34],"solution":[36,63,118,220],"based":[37,187],"on":[38,188],"previously":[39,65,120],"generated":[40,66,121],"different":[41],"candidate":[42,52,67,122],"solutions.":[44,69,124],"have":[47],"two":[48],"steps:":[49],"generating":[50],"multiple":[51],"solutions":[54],"from":[55,64,119],"forming":[59],"a":[60,181],"final":[61,218],"problem":[71,102,206],"first":[74,205],"step":[75,106,230],"text":[78,93,137],"representation,":[79],"where":[80],"word":[81,131],"frequencies":[82,132],"are":[83,99],"often":[84],"used":[85],"as":[86,95,133],"features.":[87],"Other":[88],"semantic":[89,159,198],"information":[90,146,160,199],"such":[94],"topics,":[96],"hypertext,":[97,149],"etc":[98],"ignored.":[100],"The":[101,153,210,239],"for":[103],"second":[105,229,237],"that":[108,242],"current":[110],"popular":[111],"median":[112],"partition":[113],"approach":[114,129,156,214],"selects":[115],"common":[126],"ensemble":[128,155,185,252],"uses":[130],"features":[134],"represent":[136],"(documents).":[139],"However,":[140],"documents":[141,163],"usually":[142],"contain":[143],"semantically":[144],"rich":[145],"i.e.":[147],"words,":[148],"titles,":[150],"topics":[151],"etc.":[152],"cluster":[154,211],"ignores":[157],"hence":[165],"prone":[167],"produce":[169],"futile":[170],"groupings":[171],"documents.":[174],"In":[175],"this":[176],"research":[177],"work,":[178],"we":[179],"present":[180],"new":[182,244],"multi-objective":[183],"method":[186,195,233,245],"Strength":[189],"Pareto":[190],"Evolutionary":[191],"Algorithm":[192],"(SPEA-II).":[193],"Our":[194],"utilizes":[196],"(rich":[200],"features)":[201],"address":[203,235],"ensembles.":[209],"oriented":[212],"evolutionary":[213],"derives":[216],"by":[221],"selecting":[222],"better":[223,247],"quality":[224],"clusters":[225],"our":[232,243],"problem.":[238],"results":[240,248],"show":[241],"provides":[246],"than":[249],"other":[250],"methods.":[253]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
