{"id":"https://openalex.org/W4206441775","doi":"https://doi.org/10.1109/bigdata52589.2021.9671297","title":"Random Sample Partition-Based Clustering Ensemble Algorithm for Big Data","display_name":"Random Sample Partition-Based Clustering Ensemble Algorithm for Big Data","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4206441775","doi":"https://doi.org/10.1109/bigdata52589.2021.9671297"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9671297","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671297","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"article","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/A5100840818","display_name":"Xueqin Du","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xueqin Du","raw_affiliation_strings":["College of Computer Science & Software Engineering, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science & Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076542236","display_name":"Yulin He","orcid":"https://orcid.org/0000-0002-3415-0686"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yulin He","raw_affiliation_strings":["College of Computer Science & Software Engineering, Shenzhen University, Shenzhen, China","National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science & Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003347359","display_name":"Joshua Zhexue Huang","orcid":"https://orcid.org/0000-0002-6797-2571"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Joshua Zhexue Huang","raw_affiliation_strings":["College of Computer Science & Software Engineering, Shenzhen University, Shenzhen, China","National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science & Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100840818"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":1.0053,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.80276687,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"5885","last_page":"5887"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9980999827384949,"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":0.9980999827384949,"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/T10057","display_name":"Face and Expression Recognition","score":0.9872999787330627,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9836000204086304,"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":0.8927366733551025},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.6992875337600708},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.6861346960067749},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.6054858565330505},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5907605290412903},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.5785809755325317},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5557563900947571},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5377111434936523},{"id":"https://openalex.org/keywords/single-linkage-clustering","display_name":"Single-linkage clustering","score":0.5113029479980469},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.4386708438396454},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.41708552837371826},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4144873023033142},{"id":"https://openalex.org/keywords/k-medians-clustering","display_name":"k-medians clustering","score":0.4108910858631134},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34644997119903564},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26662683486938477}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8927366733551025},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.6992875337600708},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.6861346960067749},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.6054858565330505},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5907605290412903},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.5785809755325317},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5557563900947571},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5377111434936523},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.5113029479980469},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.4386708438396454},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.41708552837371826},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4144873023033142},{"id":"https://openalex.org/C115328559","wikidata":"https://www.wikidata.org/wiki/Q4041956","display_name":"k-medians clustering","level":5,"score":0.4108910858631134},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34644997119903564},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26662683486938477}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9671297","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671297","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2108343180","https://openalex.org/W2114979880","https://openalex.org/W2139280638","https://openalex.org/W2295256067","https://openalex.org/W2551879329","https://openalex.org/W2773612851","https://openalex.org/W2952171869","https://openalex.org/W6729788535"],"related_works":["https://openalex.org/W2389934482","https://openalex.org/W3176177124","https://openalex.org/W4241252752","https://openalex.org/W2356030476","https://openalex.org/W2590117803","https://openalex.org/W2185743328","https://openalex.org/W4310575853","https://openalex.org/W1491908038","https://openalex.org/W2046825742","https://openalex.org/W2573408520"],"abstract_inverted_index":{"A":[0],"novel":[1],"random":[2],"sample":[3,62],"partition-based":[4],"clustering":[5,19,33,42,54,77,86,101,148],"ensemble":[6,102],"(RSP-CE)":[7],"algorithm":[8,112,137],"is":[9,138],"proposed":[10],"in":[11,26,95],"this":[12],"paper":[13],"to":[14,83,142],"handle":[15],"the":[16,31,40,52,60,65,72,85,114,127,145],"big":[17,67,90,106,146],"data":[18,37,57,68,81,107,147],"problems.":[20,149],"There":[21],"are":[22],"three":[23],"key":[24],"components":[25],"RSP-CE":[27,111,136],"algorithm,":[28],"i.e.,":[29],"generating":[30],"base":[32,76],"results":[34,43,78,94],"on":[35,79,88,104],"RSP":[36,53,56],"blocks,":[38],"harmonizing":[39],"based":[41],"with":[44,64,97,126,144],"maximum":[45],"mean":[46],"discrepancy":[47],"(MMD)":[48],"criterion,":[49],"and":[50,69,121,132],"refining":[51],"results.":[55],"blocks":[58],"have":[59],"consistent":[61],"distributions":[63],"whole":[66,89],"thus":[70,133],"provide":[71],"possibility":[73],"for":[74],"using":[75],"different":[80],"subsets":[82],"approximate":[84],"result":[87],"data.":[91],"The":[92],"experimental":[93],"comparison":[96],"other":[98],"5":[99],"well-known":[100],"algorithms":[103],"4":[105],"sets":[108],"show":[109],"that":[110,135],"obtains":[113],"better":[115],"normalized":[116],"mutual":[117],"information":[118],"(NMI)":[119],"values":[120,125],"Fowlkes-Mallows":[122],"Index":[123],"(FMI)":[124],"less":[128],"training":[129],"time":[130],"consumptions":[131],"demonstrate":[134],"a":[139],"viable":[140],"approach":[141],"deal":[143]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
