{"id":"https://openalex.org/W3081351623","doi":"https://doi.org/10.1109/tnnls.2020.3015795","title":"Fast and Effective Active Clustering Ensemble Based on Density Peak","display_name":"Fast and Effective Active Clustering Ensemble Based on Density Peak","publication_year":2020,"publication_date":"2020-08-26","ids":{"openalex":"https://openalex.org/W3081351623","doi":"https://doi.org/10.1109/tnnls.2020.3015795","mag":"3081351623","pmid":"https://pubmed.ncbi.nlm.nih.gov/32845845"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2020.3015795","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.3015795","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5068331721","display_name":"Yifan Shi","orcid":"https://orcid.org/0000-0001-6961-5888"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Shi","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100701158","display_name":"Zhiwen Yu","orcid":"https://orcid.org/0000-0002-0935-5890"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]},{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwen Yu","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","School of Computers, Guangdong University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-0935-5890","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"School of Computers, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100625023","display_name":"Wenming Cao","orcid":"https://orcid.org/0000-0002-6908-8018"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Wenming Cao","raw_affiliation_strings":["The University of Hong Kong, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100643265","display_name":"C. L. Philip Chen","orcid":"https://orcid.org/0000-0001-5451-7230"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"C. L. Philip Chen","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5451-7230","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014196059","display_name":"Hau\u2212San Wong","orcid":"https://orcid.org/0000-0002-1530-7529"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Hau-San Wong","raw_affiliation_strings":["City University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-1530-7529","affiliations":[{"raw_affiliation_string":"City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100682155","display_name":"Guoqiang Han","orcid":"https://orcid.org/0000-0002-9687-3900"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoqiang Han","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-9687-3900","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.6505,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.9430864,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"32","issue":"8","first_page":"3593","last_page":"3607"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9998999834060669,"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":0.9998999834060669,"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/T12761","display_name":"Data Stream Mining Techniques","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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8548816442489624},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.71988445520401},{"id":"https://openalex.org/keywords/representativeness-heuristic","display_name":"Representativeness heuristic","score":0.6507897973060608},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6108573079109192},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6107609272003174},{"id":"https://openalex.org/keywords/consensus-clustering","display_name":"Consensus clustering","score":0.5501193404197693},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.5407806038856506},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.49521604180336},{"id":"https://openalex.org/keywords/constrained-clustering","display_name":"Constrained clustering","score":0.4580513536930084},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.4564497470855713},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.43894466757774353},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.4366689622402191},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.41443219780921936},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3829546570777893},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.355914831161499},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13515758514404297},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08052748441696167}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8548816442489624},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.71988445520401},{"id":"https://openalex.org/C37381756","wikidata":"https://www.wikidata.org/wiki/Q20203288","display_name":"Representativeness heuristic","level":2,"score":0.6507897973060608},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6108573079109192},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6107609272003174},{"id":"https://openalex.org/C186767784","wikidata":"https://www.wikidata.org/wiki/Q5162841","display_name":"Consensus clustering","level":5,"score":0.5501193404197693},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.5407806038856506},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.49521604180336},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.4580513536930084},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.4564497470855713},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.43894466757774353},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.4366689622402191},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.41443219780921936},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3829546570777893},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.355914831161499},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13515758514404297},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08052748441696167},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2020.3015795","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.3015795","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:32845845","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32845845","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3677684130","display_name":null,"funder_award_id":"61722205","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5197980865","display_name":null,"funder_award_id":"2019YFA0706200","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5436807578","display_name":null,"funder_award_id":"2019YFB1703600","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G653700208","display_name":null,"funder_award_id":"61751202","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6741110764","display_name":null,"funder_award_id":"61702195","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7611596349","display_name":null,"funder_award_id":"61751205","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":95,"referenced_works":["https://openalex.org/W137313310","https://openalex.org/W144691381","https://openalex.org/W203257931","https://openalex.org/W1416232810","https://openalex.org/W1517123091","https://openalex.org/W1532264762","https://openalex.org/W1556219185","https://openalex.org/W1562197959","https://openalex.org/W1875623881","https://openalex.org/W1934973097","https://openalex.org/W1965450189","https://openalex.org/W1966162499","https://openalex.org/W1967260758","https://openalex.org/W1974758710","https://openalex.org/W1983619063","https://openalex.org/W1987839426","https://openalex.org/W1988735952","https://openalex.org/W1995692149","https://openalex.org/W1996141584","https://openalex.org/W1997996331","https://openalex.org/W1999365490","https://openalex.org/W2006251480","https://openalex.org/W2012878613","https://openalex.org/W2039786238","https://openalex.org/W2051549110","https://openalex.org/W2053415806","https://openalex.org/W2054528501","https://openalex.org/W2072613728","https://openalex.org/W2074166357","https://openalex.org/W2075604337","https://openalex.org/W2091469633","https://openalex.org/W2097820631","https://openalex.org/W2098029000","https://openalex.org/W2100346396","https://openalex.org/W2101234009","https://openalex.org/W2105268089","https://openalex.org/W2107480077","https://openalex.org/W2111004121","https://openalex.org/W2116810533","https://openalex.org/W2118590858","https://openalex.org/W2122644269","https://openalex.org/W2127939112","https://openalex.org/W2131365923","https://openalex.org/W2134089414","https://openalex.org/W2134342006","https://openalex.org/W2134370969","https://openalex.org/W2135076825","https://openalex.org/W2135914502","https://openalex.org/W2139280638","https://openalex.org/W2142838865","https://openalex.org/W2150143163","https://openalex.org/W2153839362","https://openalex.org/W2162009590","https://openalex.org/W2162506329","https://openalex.org/W2165835468","https://openalex.org/W2170584976","https://openalex.org/W2252984395","https://openalex.org/W2262682506","https://openalex.org/W2298199500","https://openalex.org/W2483766645","https://openalex.org/W2528144111","https://openalex.org/W2605427894","https://openalex.org/W2753324760","https://openalex.org/W2771379243","https://openalex.org/W2789712634","https://openalex.org/W2792823099","https://openalex.org/W2800791174","https://openalex.org/W2804847616","https://openalex.org/W2805867381","https://openalex.org/W2899106589","https://openalex.org/W2899771611","https://openalex.org/W2911754149","https://openalex.org/W2920782659","https://openalex.org/W2953328903","https://openalex.org/W2963325132","https://openalex.org/W2963822124","https://openalex.org/W2963976838","https://openalex.org/W2964051179","https://openalex.org/W3100648197","https://openalex.org/W3120740533","https://openalex.org/W4285719527","https://openalex.org/W6608319409","https://openalex.org/W6631721778","https://openalex.org/W6633883679","https://openalex.org/W6640443130","https://openalex.org/W6663082325","https://openalex.org/W6674539747","https://openalex.org/W6675354045","https://openalex.org/W6676032131","https://openalex.org/W6676085107","https://openalex.org/W6676671362","https://openalex.org/W6679849079","https://openalex.org/W6691212913","https://openalex.org/W6697721707","https://openalex.org/W6756040250"],"related_works":["https://openalex.org/W2111827030","https://openalex.org/W4237106426","https://openalex.org/W2564198485","https://openalex.org/W3035964814","https://openalex.org/W1577058187","https://openalex.org/W3186815950","https://openalex.org/W3124860551","https://openalex.org/W2040929534","https://openalex.org/W2311450085","https://openalex.org/W2309230723"],"abstract_inverted_index":{"Semisupervised":[0],"clustering":[1,21,50,65,91,108,140],"methods":[2,37,148,151],"improve":[3],"performance":[4],"by":[5,30,145],"randomly":[6],"selecting":[7],"pairwise":[8,33],"constraints,":[9],"which":[10],"may":[11],"lead":[12],"to":[13,24,51,77,86,98,117],"redundancy":[14],"and":[15,46,71,114],"instability.":[16],"In":[17,54,102],"this":[18,55],"context,":[19],"active":[20,61,107],"is":[22,134],"proposed":[23],"maximize":[25],"the":[26,43,88,119,127,159],"efficacy":[27],"of":[28,42,90,139,161],"annotations":[29],"effectively":[31],"using":[32],"constraints.":[34],"However,":[35],"existing":[36],"lack":[38],"an":[39,60,106],"overall":[40],"consideration":[41],"querying":[44],"criteria":[45],"repeatedly":[47],"run":[48],"semisupervised":[49],"update":[52,99],"labels.":[53],"work,":[56],"we":[57,94,104],"first":[58],"propose":[59,105],"density":[62],"peak":[63],"(ADP)":[64],"algorithm":[66],"that":[67,111],"considers":[68],"both":[69],"representativeness":[70],"informativeness.":[72],"Representative":[73],"instances":[74,83,122],"are":[75,84],"selected":[76],"capture":[78],"data":[79,154],"patterns,":[80],"while":[81],"informative":[82],"queried":[85],"reduce":[87],"uncertainty":[89],"results.":[92,141],"Meanwhile,":[93],"design":[95],"a":[96],"fast-update-strategy":[97],"labels":[100],"efficiently.":[101],"addition,":[103],"ensemble":[109],"framework":[110],"combines":[112],"local":[113],"global":[115],"uncertainties":[116],"query":[118],"most":[120],"ambiguous":[121],"for":[123,136],"better":[124,137],"separation":[125],"between":[126],"clusters.":[128],"A":[129],"weighted":[130],"voting":[131],"consensus":[132],"method":[133],"introduced":[135],"integration":[138],"We":[142],"conducted":[143],"experiments":[144],"comparing":[146],"our":[147,162],"with":[149],"state-of-the-art":[150],"on":[152],"real-world":[153],"sets.":[155],"Experimental":[156],"results":[157],"demonstrate":[158],"effectiveness":[160],"methods.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}