{"id":"https://openalex.org/W3089672940","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207377","title":"AUC Estimation and Concept Drift Detection for Imbalanced Data Streams with Multiple Classes","display_name":"AUC Estimation and Concept Drift Detection for Imbalanced Data Streams with Multiple Classes","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3089672940","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207377","mag":"3089672940"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9207377","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207377","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://research.birmingham.ac.uk/en/publications/313ff4ad-969d-4e2c-bef6-877042ef8caa","any_repository_has_fulltext":true},"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":["School of Computer Science, University of Birmingham, Birmingham, UK"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Birmingham, Birmingham, UK","institution_ids":["https://openalex.org/I79619799"]}]},{"author_position":"last","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":["School of Computer Science, University of Birmingham, Birmingham, UK"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Birmingham, Birmingham, UK","institution_ids":["https://openalex.org/I79619799"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100400186"],"corresponding_institution_ids":["https://openalex.org/I79619799"],"apc_list":null,"apc_paid":null,"fwci":2.5707,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.91769488,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"2020","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":1.0,"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/T12761","display_name":"Data Stream Mining Techniques","score":1.0,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.989799976348877,"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":0.9848999977111816,"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/concept-drift","display_name":"Concept drift","score":0.9695241451263428},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.7896856069564819},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7729453444480896},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6194238662719727},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6069697141647339},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.5846980214118958},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5658475160598755},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5565057396888733},{"id":"https://openalex.org/keywords/streams","display_name":"STREAMS","score":0.5169231295585632}],"concepts":[{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.9695241451263428},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.7896856069564819},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7729453444480896},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6194238662719727},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6069697141647339},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.5846980214118958},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5658475160598755},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5565057396888733},{"id":"https://openalex.org/C42090638","wikidata":"https://www.wikidata.org/wiki/Q4048907","display_name":"STREAMS","level":2,"score":0.5169231295585632},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9207377","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207377","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/313ff4ad-969d-4e2c-bef6-877042ef8caa","is_oa":true,"landing_page_url":"https://research.birmingham.ac.uk/en/publications/313ff4ad-969d-4e2c-bef6-877042ef8caa","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Wang, S & Minku, L 2020, AUC estimation and concept drift detection for imbalanced data streams with multiple classes. in Proceedings of the International Joint Conference on Neural Networks (IJCNN), World Congress on Computational Intelligence, 2020., 9207377, Proceedings of International Joint Conference on Neural Networks, IEEE Computer Society Press, IEEE International Joint Conference on Neural Networks (IJCNN), 2020 , Glasgow, United Kingdom, 19/07/20. https://doi.org/10.1109/IJCNN48605.2020.9207377","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:pure.atira.dk:publications/313ff4ad-969d-4e2c-bef6-877042ef8caa","is_oa":false,"landing_page_url":"https://research.birmingham.ac.uk/portal/en/publications/auc-estimation-and-concept-drift-detection-for-imbalanced-data-streams-with-multiple-classes(313ff4ad-969d-4e2c-bef6-877042ef8caa).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":"","raw_type":""},{"id":"mag:3201532053","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002262892702768","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/313ff4ad-969d-4e2c-bef6-877042ef8caa","is_oa":true,"landing_page_url":"https://research.birmingham.ac.uk/en/publications/313ff4ad-969d-4e2c-bef6-877042ef8caa","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Wang, S & Minku, L 2020, AUC estimation and concept drift detection for imbalanced data streams with multiple classes. in Proceedings of the International Joint Conference on Neural Networks (IJCNN), World Congress on Computational Intelligence, 2020., 9207377, Proceedings of International Joint Conference on Neural Networks, IEEE Computer Society Press, IEEE International Joint Conference on Neural Networks (IJCNN), 2020 , Glasgow, United Kingdom, 19/07/20. https://doi.org/10.1109/IJCNN48605.2020.9207377","raw_type":"contributionToPeriodical"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1484011530","https://openalex.org/W1509515766","https://openalex.org/W1529840045","https://openalex.org/W1605695115","https://openalex.org/W1850407572","https://openalex.org/W1904826605","https://openalex.org/W1912982817","https://openalex.org/W1972027649","https://openalex.org/W2022851810","https://openalex.org/W2024223694","https://openalex.org/W2047449506","https://openalex.org/W2051903196","https://openalex.org/W2053472607","https://openalex.org/W2082168306","https://openalex.org/W2101195239","https://openalex.org/W2118978333","https://openalex.org/W2123003172","https://openalex.org/W2125517959","https://openalex.org/W2135493362","https://openalex.org/W2188660960","https://openalex.org/W2461041754","https://openalex.org/W2526823171","https://openalex.org/W2577513693","https://openalex.org/W2587314106","https://openalex.org/W2604756720","https://openalex.org/W2794290001","https://openalex.org/W6727744306"],"related_works":["https://openalex.org/W4307392573","https://openalex.org/W2802243998","https://openalex.org/W2736127210","https://openalex.org/W2329342202","https://openalex.org/W2574092225","https://openalex.org/W4200217704","https://openalex.org/W2161835057","https://openalex.org/W1521014365","https://openalex.org/W2740428142","https://openalex.org/W2187127952"],"abstract_inverted_index":{"Online":[0],"class":[1,11],"imbalance":[2,53],"learning":[3,14,91],"deals":[4],"with":[5,146],"data":[6,16,88,111,139,144],"streams":[7,112,140],"having":[8],"very":[9],"skewed":[10],"distributions.":[12],"When":[13],"from":[15],"streams,":[17],"concept":[18,40,58,123,132],"drift":[19,41,59,133],"is":[20,152],"one":[21],"of":[22,75,137],"the":[23,28,72],"major":[24],"challenges":[25,56],"that":[26],"deteriorate":[27],"classification":[29],"performance.":[30],"Although":[31],"several":[32],"approaches":[33],"have":[34],"been":[35],"recently":[36],"proposed":[37,94],"to":[38,49,121,154],"overcome":[39],"in":[42,57,89,130,134],"imbalanced":[43,69,87],"data,":[44],"they":[45,117],"are":[46,100],"all":[47],"limited":[48,73],"two-class":[50],"cases.":[51],"Multi-class":[52],"imposes":[54],"additional":[55],"detection":[60],"and":[61,71,98,113,115,141,158],"performance":[62,76],"evaluation,":[63],"such":[64],"as":[65],"a":[66,135,142],"more":[67],"severe":[68],"distribution":[70],"choice":[74],"measures.":[77],"This":[78],"paper":[79],"extends":[80],"AUC":[81],"for":[82],"evaluating":[83],"classifiers":[84],"on":[85,106,109],"multi-class":[86],"online":[90],"scenarios.":[92],"The":[93,125],"metrics,":[95],"PMAUC,":[96],"WAUC":[97],"EWAUC,":[99],"studied":[101],"through":[102],"comprehensive":[103],"experiments,":[104],"focusing":[105],"their":[107],"characteristics":[108],"time-changing":[110],"whether":[114],"how":[116],"can":[118],"be":[119,155],"used":[120],"detect":[122],"drift.":[124],"AUC-based":[126],"metrics":[127],"show":[128],"effectiveness":[129],"detecting":[131],"variety":[136],"artificial":[138],"real-world":[143],"application":[145],"multiple":[147],"classes.":[148],"In":[149],"particular,":[150],"EWAUC":[151],"shown":[153],"both":[156],"effective":[157],"efficient.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
