{"id":"https://openalex.org/W2007797768","doi":"https://doi.org/10.1142/s1469026813400014","title":"ONLINE CLASS IMBALANCE LEARNING AND ITS APPLICATIONS IN FAULT DETECTION","display_name":"ONLINE CLASS IMBALANCE LEARNING AND ITS APPLICATIONS IN FAULT DETECTION","publication_year":2013,"publication_date":"2013-12-01","ids":{"openalex":"https://openalex.org/W2007797768","doi":"https://doi.org/10.1142/s1469026813400014","mag":"2007797768"},"language":"en","primary_location":{"id":"doi:10.1142/s1469026813400014","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1469026813400014","pdf_url":null,"source":{"id":"https://openalex.org/S206936884","display_name":"International Journal of Computational Intelligence and Applications","issn_l":"1469-0268","issn":["1469-0268","1757-5885"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311754","host_organization_name":"Imperial College Press","host_organization_lineage":["https://openalex.org/P4310311754"],"host_organization_lineage_names":["Imperial College Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence and Applications","raw_type":"journal-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/A5100400186","display_name":"Shuo Wang","orcid":"https://orcid.org/0000-0003-1380-6428"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"SHUO WANG","raw_affiliation_strings":["CERCIA, School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK"],"affiliations":[{"raw_affiliation_string":"CERCIA, School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK","institution_ids":["https://openalex.org/I79619799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064089961","display_name":"Leandro L. Minku","orcid":"https://orcid.org/0000-0002-2639-0671"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"LEANDRO L. MINKU","raw_affiliation_strings":["CERCIA, School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK"],"affiliations":[{"raw_affiliation_string":"CERCIA, School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK","institution_ids":["https://openalex.org/I79619799"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100635494","display_name":"Xin Yao","orcid":"https://orcid.org/0000-0001-8837-4442"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"XIN YAO","raw_affiliation_strings":["CERCIA, School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK"],"affiliations":[{"raw_affiliation_string":"CERCIA, School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK","institution_ids":["https://openalex.org/I79619799"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100400186"],"corresponding_institution_ids":["https://openalex.org/I79619799"],"apc_list":null,"apc_paid":null,"fwci":11.0604,"has_fulltext":false,"cited_by_count":81,"citation_normalized_percentile":{"value":0.98213893,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"12","issue":"04","first_page":"1340001","last_page":"1340001"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9994999766349792,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9994999766349792,"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":0.9973000288009644,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.995199978351593,"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/undersampling","display_name":"Undersampling","score":0.8926275372505188},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8902710676193237},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6603409647941589},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6315197348594666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6166542768478394},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.5547213554382324},{"id":"https://openalex.org/keywords/online-learning","display_name":"Online learning","score":0.5240849852561951},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.4333825707435608},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4322201907634735},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42115166783332825}],"concepts":[{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.8926275372505188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8902710676193237},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6603409647941589},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6315197348594666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6166542768478394},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.5547213554382324},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.5240849852561951},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.4333825707435608},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4322201907634735},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42115166783332825},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1142/s1469026813400014","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1469026813400014","pdf_url":null,"source":{"id":"https://openalex.org/S206936884","display_name":"International Journal of Computational Intelligence and Applications","issn_l":"1469-0268","issn":["1469-0268","1757-5885"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311754","host_organization_name":"Imperial College Press","host_organization_lineage":["https://openalex.org/P4310311754"],"host_organization_lineage_names":["Imperial College Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence and Applications","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/750a688a-7dd7-479d-996d-0fbb65365116","is_oa":false,"landing_page_url":"https://research.birmingham.ac.uk/portal/en/publications/online-class-imbalance-learning-and-its-applications-in-fault-detection(750a688a-7dd7-479d-996d-0fbb65365116).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Wang, S, Minku, L & Yao, X 2013, 'Online Class Imbalance Learning and Its Applications in Fault Detection', International Journal of Computational Intelligence and Applications, vol. 12, no. 4, 1340001. https://doi.org/10.1142/S1469026813400014","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320006","display_name":"Royal Society","ror":"https://ror.org/03wnrjx87"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W21288262","https://openalex.org/W64908097","https://openalex.org/W85350352","https://openalex.org/W130071847","https://openalex.org/W144837275","https://openalex.org/W167016754","https://openalex.org/W168970045","https://openalex.org/W1503432700","https://openalex.org/W1505648523","https://openalex.org/W1529840045","https://openalex.org/W1563938718","https://openalex.org/W1577965913","https://openalex.org/W1964962870","https://openalex.org/W1965895350","https://openalex.org/W1972113839","https://openalex.org/W2009727399","https://openalex.org/W2010657328","https://openalex.org/W2012663856","https://openalex.org/W2012852390","https://openalex.org/W2037242621","https://openalex.org/W2042593695","https://openalex.org/W2052300809","https://openalex.org/W2072135972","https://openalex.org/W2074805796","https://openalex.org/W2078885513","https://openalex.org/W2083551746","https://openalex.org/W2086075853","https://openalex.org/W2088220893","https://openalex.org/W2093919988","https://openalex.org/W2100915909","https://openalex.org/W2105531169","https://openalex.org/W2118978333","https://openalex.org/W2119191234","https://openalex.org/W2120457925","https://openalex.org/W2120705090","https://openalex.org/W2123003172","https://openalex.org/W2124288185","https://openalex.org/W2124725986","https://openalex.org/W2139327121","https://openalex.org/W2148143831","https://openalex.org/W2155806188","https://openalex.org/W2156820010","https://openalex.org/W2158896888","https://openalex.org/W2162006657","https://openalex.org/W2166781513","https://openalex.org/W2172005224","https://openalex.org/W2912934387"],"related_works":["https://openalex.org/W2109073422","https://openalex.org/W2887783772","https://openalex.org/W2101754595","https://openalex.org/W4249381695","https://openalex.org/W2534887053","https://openalex.org/W2026172757","https://openalex.org/W2080076470","https://openalex.org/W4389292014","https://openalex.org/W2394059563","https://openalex.org/W2017942469"],"abstract_inverted_index":{"Although":[0],"class":[1,16,39,76,98,113,164],"imbalance":[2,17,77,99],"learning":[3,6,18,78,88,151],"and":[4,50,62,106,121,146],"online":[5,15,75,87,91,172],"have":[7],"been":[8],"extensively":[9],"studied":[10],"in":[11,53,58,125,163,166],"the":[12,21,82,136],"literature":[13],"separately,":[14],"that":[19,132],"considers":[20],"challenges":[22],"of":[23,45,68,114],"both":[24],"fields":[25],"has":[26],"not":[27],"drawn":[28],"much":[29],"attention.":[30],"It":[31],"deals":[32],"with":[33],"data":[34,117,144,154],"streams":[35],"having":[36],"very":[37,140],"skewed":[38],"distributions,":[40],"such":[41],"as":[42],"fault":[43,115],"diagnosis":[44],"real-time":[46],"control":[47],"monitoring":[48],"systems":[49],"intrusion":[51],"detection":[52,116],"computer":[54],"networks.":[55],"To":[56],"fill":[57],"this":[59,71],"research":[60],"gap":[61],"contribute":[63],"to":[64,96,160],"a":[65,85,112],"wide":[66],"range":[67],"real-world":[69],"applications,":[70],"paper":[72],"first":[73],"formulates":[74],"problems.":[79],"Based":[80],"on":[81],"problem":[83],"formulation,":[84],"new":[86],"algorithm,":[89],"sampling-based":[90],"bagging":[92,173],"(SOB),":[93],"is":[94,158,175],"proposed":[95],"tackle":[97],"adaptively.":[100],"Then,":[101],"we":[102,130],"study":[103],"how":[104],"SOB":[105,133],"other":[107],"state-of-the-art":[108],"methods":[109],"can":[110,134],"benefit":[111],"under":[118],"various":[119],"scenarios":[120],"analyze":[122],"their":[123],"performance":[124,137],"depth.":[126],"Through":[127],"extensive":[128],"experiments,":[129],"find":[131],"balance":[135],"between":[138],"classes":[139],"well":[141],"across":[142],"different":[143],"domains":[145],"produce":[147],"stable":[148],"G-mean":[149],"when":[150],"constantly":[152],"imbalanced":[153],"streams,":[155],"but":[156],"it":[157],"sensitive":[159],"sudden":[161],"changes":[162],"imbalance,":[165],"which":[167],"case":[168],"SOB's":[169],"predecessor":[170],"undersampling-based":[171],"(UOB)":[174],"more":[176],"robust.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":11},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
