{"id":"https://openalex.org/W2987491803","doi":"https://doi.org/10.1145/3363573","title":"Multi-Label Punitive kNN with Self-Adjusting Memory for Drifting Data Streams","display_name":"Multi-Label Punitive kNN with Self-Adjusting Memory for Drifting Data Streams","publication_year":2019,"publication_date":"2019-11-11","ids":{"openalex":"https://openalex.org/W2987491803","doi":"https://doi.org/10.1145/3363573","mag":"2987491803"},"language":"en","primary_location":{"id":"doi:10.1145/3363573","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3363573","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","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/A5043305725","display_name":"Martha Roseberry","orcid":"https://orcid.org/0000-0002-0848-9790"},"institutions":[{"id":"https://openalex.org/I184840846","display_name":"Virginia Commonwealth University","ror":"https://ror.org/02nkdxk79","country_code":"US","type":"education","lineage":["https://openalex.org/I184840846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Martha Roseberry","raw_affiliation_strings":["Virginia Commonwealth University, Richmond, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Commonwealth University, Richmond, VA, USA","institution_ids":["https://openalex.org/I184840846"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054879396","display_name":"Bartosz Krawczyk","orcid":"https://orcid.org/0000-0002-9774-0106"},"institutions":[{"id":"https://openalex.org/I184840846","display_name":"Virginia Commonwealth University","ror":"https://ror.org/02nkdxk79","country_code":"US","type":"education","lineage":["https://openalex.org/I184840846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bartosz Krawczyk","raw_affiliation_strings":["Virginia Commonwealth University, Richmond, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Commonwealth University, Richmond, VA, USA","institution_ids":["https://openalex.org/I184840846"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009379305","display_name":"Alberto Cano","orcid":"https://orcid.org/0000-0001-9027-298X"},"institutions":[{"id":"https://openalex.org/I184840846","display_name":"Virginia Commonwealth University","ror":"https://ror.org/02nkdxk79","country_code":"US","type":"education","lineage":["https://openalex.org/I184840846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alberto Cano","raw_affiliation_strings":["Virginia Commonwealth University, Richmond, VA, USA"],"raw_orcid":"https://orcid.org/0000-0001-9027-298X","affiliations":[{"raw_affiliation_string":"Virginia Commonwealth University, Richmond, VA, USA","institution_ids":["https://openalex.org/I184840846"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.326,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.93990582,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"13","issue":"6","first_page":"1","last_page":"31"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9927999973297119,"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":0.9911999702453613,"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/computer-science","display_name":"Computer science","score":0.8351473212242126},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.7991793155670166},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.6994186639785767},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5707386136054993},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5648292899131775},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47064274549484253},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.45054399967193604},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4498641788959503}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8351473212242126},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.7991793155670166},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.6994186639785767},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5707386136054993},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5648292899131775},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47064274549484253},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.45054399967193604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4498641788959503},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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":1,"locations":[{"id":"doi:10.1145/3363573","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3363573","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":78,"referenced_works":["https://openalex.org/W1506859583","https://openalex.org/W1529840045","https://openalex.org/W1585854823","https://openalex.org/W1679418795","https://openalex.org/W1953606363","https://openalex.org/W1969574535","https://openalex.org/W1982039810","https://openalex.org/W1999954155","https://openalex.org/W2000454347","https://openalex.org/W2009727399","https://openalex.org/W2010657328","https://openalex.org/W2022477494","https://openalex.org/W2029517229","https://openalex.org/W2032028573","https://openalex.org/W2038624061","https://openalex.org/W2052684427","https://openalex.org/W2075457099","https://openalex.org/W2094047042","https://openalex.org/W2123217057","https://openalex.org/W2133223948","https://openalex.org/W2136246134","https://openalex.org/W2143991132","https://openalex.org/W2145827727","https://openalex.org/W2171809276","https://openalex.org/W2191619632","https://openalex.org/W2216573287","https://openalex.org/W2338318698","https://openalex.org/W2343252634","https://openalex.org/W2344964031","https://openalex.org/W2434851943","https://openalex.org/W2470642288","https://openalex.org/W2507677290","https://openalex.org/W2509304078","https://openalex.org/W2528421823","https://openalex.org/W2550035969","https://openalex.org/W2582292785","https://openalex.org/W2584444914","https://openalex.org/W2585508806","https://openalex.org/W2585528949","https://openalex.org/W2588336250","https://openalex.org/W2604756720","https://openalex.org/W2606819545","https://openalex.org/W2612063921","https://openalex.org/W2626498001","https://openalex.org/W2727662945","https://openalex.org/W2727699974","https://openalex.org/W2739512903","https://openalex.org/W2743621318","https://openalex.org/W2754319208","https://openalex.org/W2754445604","https://openalex.org/W2754697883","https://openalex.org/W2767272762","https://openalex.org/W2771828150","https://openalex.org/W2773675312","https://openalex.org/W2783366437","https://openalex.org/W2784762165","https://openalex.org/W2785173328","https://openalex.org/W2790031975","https://openalex.org/W2799399089","https://openalex.org/W2803163484","https://openalex.org/W2883654649","https://openalex.org/W2890848540","https://openalex.org/W2895667350","https://openalex.org/W2896153502","https://openalex.org/W2897069058","https://openalex.org/W2897147406","https://openalex.org/W2901168609","https://openalex.org/W2905233574","https://openalex.org/W2914973938","https://openalex.org/W2941819655","https://openalex.org/W2942354300","https://openalex.org/W2962805619","https://openalex.org/W2964491809","https://openalex.org/W3003253354","https://openalex.org/W4243367342","https://openalex.org/W4256361765","https://openalex.org/W4297978425","https://openalex.org/W6704698082"],"related_works":["https://openalex.org/W127192698","https://openalex.org/W2743735673","https://openalex.org/W2570600173","https://openalex.org/W2893008024","https://openalex.org/W2360131081","https://openalex.org/W2985941356","https://openalex.org/W4361801939","https://openalex.org/W2802243998","https://openalex.org/W1521014365","https://openalex.org/W2736127210"],"abstract_inverted_index":{"In":[0],"multi-label":[1,13,23,172,177],"learning,":[2],"data":[3,14,30,72,94,107,126,149,173],"may":[4],"simultaneously":[5],"belong":[6],"to":[7,44,79,117,122,143,163],"more":[8],"than":[9],"one":[10],"class.":[11],"When":[12],"arrives":[15],"as":[16,152],"a":[17,58,65,86,131,207],"stream,":[18],"the":[19,34,47,53,82,100,125,136,161,188],"challenges":[20],"associated":[21],"with":[22,64],"learning":[24],"are":[25,39,109],"joined":[26],"by":[27],"those":[28],"of":[29,52,187,211],"stream":[31,127,217],"mining,":[32],"including":[33],"need":[35],"for":[36,69],"algorithms":[37,165],"that":[38,108],"fast":[40],"and":[41,49,85,91,104,112,120,155,169,181,201],"flexible,":[42],"able":[43,116],"match":[45],"both":[46,110,198],"speed":[48],"evolving":[50],"nature":[51],"stream.":[54],"This":[55],"article":[56],"presents":[57],"punitive":[59,88,137],"k":[60],"nearest":[61],"neighbors":[62],"algorithm":[63],"self-adjusting":[66],"memory":[67,75,182],"(MLSAMPkNN)":[68],"multi-label,":[70],"drifting":[71],"streams.":[73],"The":[74,157,184],"adjusts":[76],"in":[77,148,215],"size":[78],"contain":[80],"only":[81,106],"current":[83,111],"concept":[84],"novel":[87],"system":[89],"identifies":[90],"penalizes":[92],"errant":[93],"examples":[95],"early,":[96],"removing":[97],"them":[98],"from":[99],"window.":[101],"By":[102],"retaining":[103],"using":[105,166],"beneficial,":[113],"MLSAMPkNN":[114,205],"is":[115,191,206],"adapt":[118],"quickly":[119],"efficiently":[121],"changes":[123],"within":[124],"while":[128],"still":[129],"maintaining":[130],"low":[132,202],"computational":[133],"complexity.":[134,204],"Additionally,":[135],"removal":[138],"mechanism":[139],"offers":[140],"increased":[141],"robustness":[142],"various":[144],"data-level":[145],"difficulties":[146],"present":[147],"streams,":[150],"such":[151],"class":[153],"imbalance":[154],"noise.":[156],"experimental":[158],"study":[159],"compares":[160],"proposal":[162],"24":[164],"30":[167],"real-world":[168],"15":[170],"artificial":[171],"streams":[174],"on":[175],"six":[176],"metrics,":[178],"evaluation":[179],"time,":[180],"consumption.":[183],"superior":[185],"performance":[186,214],"proposed":[189],"method":[190],"validated":[192],"through":[193],"non-parametric":[194],"statistical":[195],"analysis,":[196],"proving":[197],"high":[199],"accuracy":[200],"time":[203],"versatile":[208],"classifier,":[209],"capable":[210],"returning":[212],"excellent":[213],"diverse":[216],"scenarios.":[218]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
