{"id":"https://openalex.org/W4306798663","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892772","title":"Class Distribution Monitoring for Concept Drift Detection","display_name":"Class Distribution Monitoring for Concept Drift Detection","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4306798663","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892772"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892772","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892772","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2210.08470","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077218100","display_name":"Diego Stucchi","orcid":"https://orcid.org/0000-0002-8285-5285"},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Diego Stucchi","raw_affiliation_strings":["Politecnico di Milano,Milan,Italy","Politecnico di Milano, Milan, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Milano,Milan,Italy","institution_ids":["https://openalex.org/I93860229"]},{"raw_affiliation_string":"Politecnico di Milano, Milan, Italy","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009504246","display_name":"Luca Frittoli","orcid":"https://orcid.org/0000-0002-8205-4007"},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luca Frittoli","raw_affiliation_strings":["Politecnico di Milano,Milan,Italy","Politecnico di Milano, Milan, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Milano,Milan,Italy","institution_ids":["https://openalex.org/I93860229"]},{"raw_affiliation_string":"Politecnico di Milano, Milan, Italy","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006716646","display_name":"Giacomo Boracchi","orcid":"https://orcid.org/0000-0002-1650-3054"},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giacomo Boracchi","raw_affiliation_strings":["Politecnico di Milano,Milan,Italy","Politecnico di Milano, Milan, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Milano,Milan,Italy","institution_ids":["https://openalex.org/I93860229"]},{"raw_affiliation_string":"Politecnico di Milano, Milan, Italy","institution_ids":["https://openalex.org/I93860229"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077218100"],"corresponding_institution_ids":["https://openalex.org/I93860229"],"apc_list":null,"apc_paid":null,"fwci":0.4158,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.58828829,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9671000242233276,"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":0.9567999839782715,"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":0.9594708681106567},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.6510240435600281},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6412973403930664},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.5951143503189087},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.5910846590995789},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5380918383598328},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5272842049598694},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.47619736194610596},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4355087876319885},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38769465684890747},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.300936758518219},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.2222534418106079},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18023386597633362},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13577324151992798}],"concepts":[{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.9594708681106567},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.6510240435600281},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6412973403930664},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.5951143503189087},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.5910846590995789},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5380918383598328},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5272842049598694},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.47619736194610596},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4355087876319885},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38769465684890747},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.300936758518219},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.2222534418106079},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18023386597633362},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13577324151992798},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892772","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892772","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2210.08470","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.08470","pdf_url":"https://arxiv.org/pdf/2210.08470","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:re.public.polimi.it:11311/1221727","is_oa":true,"landing_page_url":"http://hdl.handle.net/11311/1221727","pdf_url":null,"source":{"id":"https://openalex.org/S4306400312","display_name":"Virtual Community of Pathological Anatomy (University of Castilla La Mancha)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79189158","host_organization_name":"University of Castilla-La Mancha","host_organization_lineage":["https://openalex.org/I79189158"],"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":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2210.08470","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.08470","pdf_url":"https://arxiv.org/pdf/2210.08470","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1457965568","https://openalex.org/W1510924833","https://openalex.org/W1565746575","https://openalex.org/W1585854823","https://openalex.org/W1965395441","https://openalex.org/W1965555277","https://openalex.org/W1992391735","https://openalex.org/W1995357300","https://openalex.org/W2033286383","https://openalex.org/W2044535354","https://openalex.org/W2058148593","https://openalex.org/W2061554433","https://openalex.org/W2069701377","https://openalex.org/W2097178527","https://openalex.org/W2099419573","https://openalex.org/W2122951085","https://openalex.org/W2150142541","https://openalex.org/W2150714037","https://openalex.org/W2767926059","https://openalex.org/W2803656225","https://openalex.org/W2887320514","https://openalex.org/W2898017895","https://openalex.org/W2901114541","https://openalex.org/W2963988108","https://openalex.org/W3021596612","https://openalex.org/W3022539872","https://openalex.org/W3089672940","https://openalex.org/W3102015031","https://openalex.org/W3104788453","https://openalex.org/W3135693966","https://openalex.org/W3175350659","https://openalex.org/W3200043934","https://openalex.org/W4248855359","https://openalex.org/W4248979535","https://openalex.org/W4253481229","https://openalex.org/W6628669898","https://openalex.org/W6635179022","https://openalex.org/W6687493607","https://openalex.org/W6688325169","https://openalex.org/W6751638136","https://openalex.org/W6801291885"],"related_works":["https://openalex.org/W2990081132","https://openalex.org/W4296984035","https://openalex.org/W4287101254","https://openalex.org/W1983393909","https://openalex.org/W2040150569","https://openalex.org/W2468095590","https://openalex.org/W2132174924","https://openalex.org/W2148298232","https://openalex.org/W1911540634","https://openalex.org/W2013909972"],"abstract_inverted_index":{"We":[0],"introduce":[1],"Class":[2],"Distribution":[3],"Monitoring":[4],"(CDM),":[5],"an":[6,27,137],"effective":[7,138],"concept-drift":[8],"detection":[9,96],"scheme":[10],"that":[11,76,110,126],"monitors":[12],"the":[13,56,78,89,99,103,112,117,129,132,141],"class-conditional":[14],"distributions":[15],"of":[16,26,131],"a":[17,38,43,82,145],"datastream.":[18],"In":[19],"particular,":[20],"our":[21],"solution":[22],"leverages":[23],"multiple":[24],"instances":[25],"online":[28],"and":[29,66,72],"nonparametric":[30],"change-detection":[31],"algorithm":[32],"based":[33],"on":[34,70],"QuantTree.":[35],"CDM":[36,85,106,127],"reports":[37],"concept":[39,57,79],"drift":[40,80,100],"after":[41],"detecting":[42],"distribution":[44],"change":[45,118,134],"in":[46],"any":[47],"class,":[48],"thus":[49],"identifying":[50],"which":[51],"classes":[52],"are":[53],"affected":[54],"by":[55],"drift.":[58],"This":[59],"can":[60],"be":[61],"precious":[62],"information":[63],"for":[64],"diagnostics":[65],"adaptation.":[67],"Our":[68],"experiments":[69],"synthetic":[71],"real-world":[73],"datastreams":[74],"show":[75],"when":[77,98,116],"affects":[81,101],"few":[83],"classes,":[84],"outperforms":[86,107],"algorithms":[87],"monitoring":[88],"overall":[90],"data":[91],"distribution,":[92],"while":[93],"achieving":[94],"similar":[95],"delays":[97],"all":[102],"classes.":[104],"Moreover,":[105],"comparable":[108],"approaches":[109],"monitor":[111],"classification":[113],"error,":[114],"particularly":[115],"is":[119],"not":[120],"very":[121],"apparent.":[122],"Finally,":[123],"we":[124],"demonstrate":[125],"inherits":[128],"properties":[130],"underlying":[133],"detector,":[135],"yielding":[136],"control":[139],"over":[140],"expected":[142],"time":[143],"before":[144],"false":[146],"alarm,":[147],"or":[148],"Average":[149],"Run":[150],"Length":[151],"(ARL":[152],"<inf":[153],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[154],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">0</inf>":[155],").":[156]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3}],"updated_date":"2026-05-06T06:03:25.996018","created_date":"2025-10-10T00:00:00"}
