{"id":"https://openalex.org/W48206859","doi":null,"title":"A comparison of resampling methods for clustering ensembles","display_name":"A comparison of resampling methods for clustering ensembles","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W48206859","mag":"48206859"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.87.8329","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.87.8329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cse.msu.edu/~minaeibi/papers/Behrouz_MLMTA2004.pdf","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5057087345","display_name":"Behrouz  Minaei Bidgoli","orcid":"https://orcid.org/0000-0002-9327-7345","observed_orcids":["https://orcid.org/0000-0002-9327-7345","https://orcid.org/0000-0001-5834-1041","https://orcid.org/0009-0007-5957-7145"]},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Behrouz Minaei-Bidgoli\u202c","raw_affiliation_strings":["Michigan State University"],"raw_orcid":"https://orcid.org/0000-0002-9327-7345","affiliations":[{"raw_affiliation_string":"Michigan State University","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038045397","display_name":"Alexander P. Topchy","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A. Topchy","raw_affiliation_strings":["Michigan State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Michigan State University","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089550786","display_name":"William F. Punch","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"William F. Punch","raw_affiliation_strings":["Computer Science and Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9077,"has_fulltext":false,"cited_by_count":71,"citation_normalized_percentile":{"value":0.93377249,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":92,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"939","last_page":"945"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9990000128746033,"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":0.9990000128746033,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.00039999998989515007,"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":9.999999747378752e-05,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/consensus-clustering","display_name":"consensus clustering","score":0.9990000128746033},{"id":"https://openalex.org/keywords/resampling","display_name":"resampling","score":0.7799999713897705},{"id":"https://openalex.org/keywords/subsampling","display_name":"subsampling","score":0.8820000290870667},{"id":"https://openalex.org/keywords/bootstrap-method","display_name":"bootstrapping","score":0.9279999732971191},{"id":"https://openalex.org/keywords/consensus-partition","display_name":"consensus partition","score":0.6520000100135803},{"id":"https://openalex.org/keywords/fusion-algorithm","display_name":"fusion algorithm","score":0.6690000295639038},{"id":"https://openalex.org/keywords/bagging","display_name":"bagging","score":0.7749999761581421},{"id":"https://openalex.org/keywords/multiple-clustering","display_name":"multiple clusterings","score":0.5139999985694885},{"id":"https://openalex.org/keywords/computational-cost-reduction","display_name":"computational complexity reduction","score":0.6240000128746033},{"id":"https://openalex.org/keywords/distributed-data-sources","display_name":"distributed data sources","score":0.8270000219345093}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7717015743255615},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.750938892364502},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6781469583511353},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.5485506653785706},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5409293174743652},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5316907167434692},{"id":"https://openalex.org/C186767784","wikidata":"https://www.wikidata.org/wiki/Q5162841","display_name":"Consensus clustering","level":5,"score":0.5061010718345642},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5030962824821472},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4890797734260559},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.45858120918273926},{"id":"https://openalex.org/C162040801","wikidata":"https://www.wikidata.org/wiki/Q799897","display_name":"Bootstrap aggregating","level":2,"score":0.44177812337875366},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.41669002175331116},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3800358474254608},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.31440383195877075},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22754895687103271},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.2081056833267212},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.87.8329","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.87.8329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cse.msu.edu/~minaeibi/papers/Behrouz_MLMTA2004.pdf","raw_type":"text"},{"id":"mag:48206859","doi":null,"is_oa":false,"landing_page_url":"http://www.lon-capa.org/papers/Behrouz_MLMTA2004.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419142","display_name":"International Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Artificial Intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W100104462","https://openalex.org/W1511827010","https://openalex.org/W1548779692","https://openalex.org/W1870625491","https://openalex.org/W2095897464","https://openalex.org/W2097645701","https://openalex.org/W2107208924","https://openalex.org/W2130851950","https://openalex.org/W2139580617","https://openalex.org/W2155081112","https://openalex.org/W2169446650","https://openalex.org/W2171903410","https://openalex.org/W2912934387"],"related_works":["https://openalex.org/W1996276996","https://openalex.org/W2155081112","https://openalex.org/W2037337722","https://openalex.org/W2131046249","https://openalex.org/W7097000855","https://openalex.org/W2977728891","https://openalex.org/W7095182094","https://openalex.org/W7097913922","https://openalex.org/W4239320016","https://openalex.org/W3023033471"],"abstract_inverted_index":{"Abstract":[0],"\u2014":[1],"Combination":[2],"of":[3,13,20,31,48,60,90,97,99,104,119,127,131,150],"multiple":[4,32,95],"clusterings":[5,96],"is":[6,107],"an":[7,87],"important":[8],"task":[9],"in":[10,37,71,124],"the":[11,18,38,49,58,117,120,125],"area":[12],"unsupervised":[14,143],"learning.":[15],"Inspired":[16],"by":[17,43],"success":[19],"supervised":[21],"bagging":[22],"algorithms,":[23],"we":[24,56],"propose":[25],"a":[26,82],"resampling":[27],"scheme":[28],"for":[29,86,141],"integration":[30],"independent":[33],"clusterings.":[34],"Individual":[35],"partitions":[36],"ensemble":[39],"are":[40],"sequentially":[41],"generated":[42],"clustering":[44,128],"specially":[45],"selected":[46],"subsamples":[47,98,112],"given":[50],"data":[51,91,122,144],"set.":[52],"In":[53],"this":[54,105],"paper,":[55],"compare":[57],"efficacy":[59],"both":[61],"subsampling":[62],"(sampling":[63],"without":[64],"replacement)":[65,69],"and":[66,138],"bootstrap":[67],"(with":[68],"techniques":[70],"conjunction":[72],"with":[73,147],"several":[74],"fusion":[75],"algorithms.":[76],"The":[77,102],"empirical":[78],"study":[79],"shows":[80],"that":[81,110],"meaningful":[83],"consensus":[84],"partition":[85],"entire":[88,121],"set":[89,123],"points":[92],"emerges":[93],"from":[94],"small":[100,111,132],"size.":[101],"purpose":[103],"paper":[106],"to":[108,115],"show":[109],"generally":[113],"suffice":[114],"represent":[116],"structure":[118],"framework":[126],"ensembles.":[129],"Subsamples":[130],"size":[133],"can":[134],"reduce":[135],"computational":[136],"cost":[137],"measurement":[139],"complexity":[140],"many":[142],"mining":[145],"tasks":[146],"distributed":[148],"sources":[149],"data.":[151]},"counts_by_year":[{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":4}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}
