{"id":"https://openalex.org/W2898517484","doi":"https://doi.org/10.1109/access.2018.2877666","title":"Two-Level-Oriented Selective Clustering Ensemble Based on Hybrid Multi-Modal Metrics","display_name":"Two-Level-Oriented Selective Clustering Ensemble Based on Hybrid Multi-Modal Metrics","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2898517484","doi":"https://doi.org/10.1109/access.2018.2877666","mag":"2898517484"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2877666","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2877666","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2877666","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070461837","display_name":"Hongling Wang","orcid":"https://orcid.org/0000-0001-5039-1298"},"institutions":[{"id":"https://openalex.org/I4210119674","display_name":"East China University of Technology","ror":"https://ror.org/027385r44","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119674"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongling Wang","raw_affiliation_strings":["School of Software, East China University of Technology, Nanchang, China"],"affiliations":[{"raw_affiliation_string":"School of Software, East China University of Technology, Nanchang, China","institution_ids":["https://openalex.org/I4210119674"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100412469","display_name":"Gang Liu","orcid":"https://orcid.org/0000-0002-9027-2485"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Liu","raw_affiliation_strings":["Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5070461837"],"corresponding_institution_ids":["https://openalex.org/I4210119674"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.6515,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77248816,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"6","issue":null,"first_page":"64159","last_page":"64168"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9995999932289124,"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":0.9995999932289124,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9861000180244446,"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":0.9821000099182129,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8808615803718567},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6939849853515625},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6367484927177429},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.6306418180465698},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.5942187905311584},{"id":"https://openalex.org/keywords/single-linkage-clustering","display_name":"Single-linkage clustering","score":0.56572425365448},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.5571938753128052},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5465043783187866},{"id":"https://openalex.org/keywords/consensus-clustering","display_name":"Consensus clustering","score":0.501345157623291},{"id":"https://openalex.org/keywords/hierarchical-clustering","display_name":"Hierarchical clustering","score":0.45318102836608887},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4490516781806946},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.44816869497299194},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.44558656215667725},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.44256192445755005},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.4296712279319763},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4113466143608093},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3830876350402832},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28765586018562317}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8808615803718567},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6939849853515625},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6367484927177429},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.6306418180465698},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.5942187905311584},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.56572425365448},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.5571938753128052},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5465043783187866},{"id":"https://openalex.org/C186767784","wikidata":"https://www.wikidata.org/wiki/Q5162841","display_name":"Consensus clustering","level":5,"score":0.501345157623291},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.45318102836608887},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4490516781806946},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.44816869497299194},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.44558656215667725},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.44256192445755005},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.4296712279319763},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4113466143608093},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3830876350402832},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28765586018562317},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2877666","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2877666","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5bf9d876be0d484483a6027fd5dadf83","is_oa":true,"landing_page_url":"https://doaj.org/article/5bf9d876be0d484483a6027fd5dadf83","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 64159-64168 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2877666","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2877666","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3564949726","display_name":null,"funder_award_id":"U1711267","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W47820314","https://openalex.org/W1448586457","https://openalex.org/W1534477342","https://openalex.org/W1570587793","https://openalex.org/W1594519403","https://openalex.org/W1599173567","https://openalex.org/W1970544520","https://openalex.org/W1993807384","https://openalex.org/W2002767255","https://openalex.org/W2011430131","https://openalex.org/W2035379061","https://openalex.org/W2043500922","https://openalex.org/W2043803919","https://openalex.org/W2061082730","https://openalex.org/W2063320116","https://openalex.org/W2070333970","https://openalex.org/W2100128988","https://openalex.org/W2107208924","https://openalex.org/W2107386336","https://openalex.org/W2111171370","https://openalex.org/W2131046249","https://openalex.org/W2139580617","https://openalex.org/W2140623944","https://openalex.org/W2142827986","https://openalex.org/W2144419338","https://openalex.org/W2150200997","https://openalex.org/W2153233077","https://openalex.org/W2155081112","https://openalex.org/W2169446650","https://openalex.org/W2193209126","https://openalex.org/W2273278181","https://openalex.org/W2287979797","https://openalex.org/W2335920499","https://openalex.org/W2357165674","https://openalex.org/W2530206022","https://openalex.org/W2576424542","https://openalex.org/W2605641866","https://openalex.org/W3083270358","https://openalex.org/W3101544696","https://openalex.org/W4239330706","https://openalex.org/W4285719527","https://openalex.org/W6601944787","https://openalex.org/W6666290978","https://openalex.org/W6685191470","https://openalex.org/W7008695577"],"related_works":["https://openalex.org/W2160785859","https://openalex.org/W2559422900","https://openalex.org/W2188840951","https://openalex.org/W2590117803","https://openalex.org/W2393707058","https://openalex.org/W2202413591","https://openalex.org/W2389934482","https://openalex.org/W2388628913","https://openalex.org/W3124860551","https://openalex.org/W2038937869"],"abstract_inverted_index":{"The":[0],"purpose":[1],"of":[2,11,47,58,74,86,103,133,146,161,214],"selective":[3,96],"clustering":[4,13,49,76,97,106,111,135,154,164,174,200],"ensemble":[5,98],"is":[6,78],"to":[7,32,41,121,129],"select":[8,198],"a":[9,94,139],"subset":[10],"base":[12,48,75,105,124,134,163,199],"partitions":[14,21,50,77,165,201],"with":[15,81,115,202],"predictive":[16],"performance":[17],"and":[18,25,45,62,83,109,159,176,205,212],"combine":[19],"these":[20,90],"into":[22],"more":[23,79],"accurate":[24],"stable":[26],"final":[27],"results.":[28],"Traditional":[29],"approaches":[30],"tend":[31],"utilize":[33],"the":[34,43,52,56,59,63,71,101,131,144,153,162,189,210,215],"well-known":[35],"validity":[36,211],"criteria":[37],"such":[38],"as":[39],"NMI":[40],"evaluate":[42],"quality":[44,132,160],"diversity":[46,82,158,204],"in":[51,127,149],"selection":[53,141,155],"process.":[54],"However,":[55],"characteristics":[57],"original":[60],"data":[61,64,177],"structure":[65],"itself":[66],"are":[67,119,166],"commonly":[68],"neglected.":[69],"Furthermore,":[70],"generation":[72],"process":[73,102],"concerned":[80],"less":[84],"consideration":[85],"quality.":[87,206],"To":[88],"tackle":[89],"problems,":[91],"we":[92,137],"propose":[93,138],"new":[95,140],"scheme.":[99,217],"In":[100,152],"generating":[104],"partitions,":[107,136],"k-means":[108,150],"hierarchical":[110],"algorithm":[112],"alternately":[113],"combined":[114],"random":[116],"projection":[117],"method":[118,191],"employed":[120],"generate":[122,195],"diverse":[123],"partitions.":[125],"Meanwhile,":[126],"order":[128],"improve":[130],"strategy":[142],"for":[143],"number":[145],"clusters":[147],"k":[148],"algorithm.":[151],"process,":[156],"both":[157,203],"evaluated":[167],"by":[168],"multi-modal":[169],"metrics":[170],"from":[171],"two":[172],"levels:":[173],"labels":[175],"structure.":[178],"Based":[179],"on":[180],"five":[181],"UCI":[182],"benchmark":[183],"datasets,":[184],"experimental":[185],"results":[186],"demonstrate":[187],"that":[188],"proposed":[190,216],"not":[192],"only":[193],"can":[194],"but":[196],"also":[197],"Experimental":[207],"analyses":[208],"show":[209],"stability":[213]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
