{"id":"https://openalex.org/W2043738837","doi":"https://doi.org/10.1145/1401890.1401987","title":"Categorizing and mining concept drifting data streams","display_name":"Categorizing and mining concept drifting data streams","publication_year":2008,"publication_date":"2008-08-24","ids":{"openalex":"https://openalex.org/W2043738837","doi":"https://doi.org/10.1145/1401890.1401987","mag":"2043738837"},"language":"en","primary_location":{"id":"doi:10.1145/1401890.1401987","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1401890.1401987","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-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/A5100364201","display_name":"Peng Zhang","orcid":"https://orcid.org/0000-0002-9603-8454"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peng Zhang","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China","Chinese Academy of Sciences , Beijing, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Chinese Academy of Sciences , Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084641325","display_name":"Xingquan Zhu","orcid":"https://orcid.org/0000-0003-4129-9611"},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xingquan Zhu","raw_affiliation_strings":["Florida Atlantic University, Boca Raton, FL, USA","Florida Atlantic University, Boca Raton, FL USA"],"affiliations":[{"raw_affiliation_string":"Florida Atlantic University, Boca Raton, FL, USA","institution_ids":["https://openalex.org/I63772739"]},{"raw_affiliation_string":"Florida Atlantic University, Boca Raton, FL USA","institution_ids":["https://openalex.org/I63772739"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113542097","display_name":"Yong Shi","orcid":"https://orcid.org/0000-0001-7974-1079"},"institutions":[{"id":"https://openalex.org/I122266389","display_name":"University of Nebraska at Omaha","ror":"https://ror.org/04yrkc140","country_code":"US","type":"education","lineage":["https://openalex.org/I122266389"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yong Shi","raw_affiliation_strings":["University of Nebraska at Omaha, Nebraska, NE, USA","University of Nebraska at Omaha, Nebraska, NE, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"University of Nebraska at Omaha, Nebraska, NE, USA","institution_ids":["https://openalex.org/I122266389"]},{"raw_affiliation_string":"University of Nebraska at Omaha, Nebraska, NE, USA#TAB#","institution_ids":["https://openalex.org/I122266389"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100364201"],"corresponding_institution_ids":["https://openalex.org/I19820366"],"apc_list":null,"apc_paid":null,"fwci":23.4635,"has_fulltext":false,"cited_by_count":97,"citation_normalized_percentile":{"value":0.99482519,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"812","last_page":"820"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9839000105857849,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.973800003528595,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/data-stream-mining","display_name":"Data stream mining","score":0.8413045406341553},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.808025062084198},{"id":"https://openalex.org/keywords/concept-drift","display_name":"Concept drift","score":0.7343806028366089},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.66845703125},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6354953050613403},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.5715120434761047},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.5116453766822815},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48442748188972473},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48135191202163696},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.4632917642593384},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32835105061531067}],"concepts":[{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.8413045406341553},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.808025062084198},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.7343806028366089},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.66845703125},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6354953050613403},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.5715120434761047},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.5116453766822815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48442748188972473},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48135191202163696},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.4632917642593384},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32835105061531067},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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":2,"locations":[{"id":"doi:10.1145/1401890.1401987","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1401890.1401987","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/28931","is_oa":false,"landing_page_url":"http://hdl.handle.net/10453/28931","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W41415572","https://openalex.org/W1548614216","https://openalex.org/W1570448133","https://openalex.org/W1575097427","https://openalex.org/W1631295847","https://openalex.org/W1907380269","https://openalex.org/W1966026565","https://openalex.org/W1990079212","https://openalex.org/W2001474264","https://openalex.org/W2009727399","https://openalex.org/W2010657328","https://openalex.org/W2028489411","https://openalex.org/W2029896651","https://openalex.org/W2030680965","https://openalex.org/W2034368206","https://openalex.org/W2068714596","https://openalex.org/W2075457099","https://openalex.org/W2096846143","https://openalex.org/W2112483442","https://openalex.org/W2118778444","https://openalex.org/W2120587290","https://openalex.org/W2122838776","https://openalex.org/W2158754421","https://openalex.org/W2169075655","https://openalex.org/W2811380766","https://openalex.org/W2966207845","https://openalex.org/W4237219250"],"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/W2161835057","https://openalex.org/W1521014365","https://openalex.org/W4200217704","https://openalex.org/W3208495060","https://openalex.org/W2740428142"],"abstract_inverted_index":{"Mining":[0],"concept":[1,41,50,62,135,214,236],"drifting":[2,42,51,63,136,215,237],"data":[3,10,88,94,115,137,141,148,178,196],"streams":[4],"is":[5,210,216,232,238],"a":[6,17,33,122,157],"defining":[7],"challenge":[8],"for":[9,170],"mining":[11,54],"research.":[12],"Recent":[13],"years":[14],"have":[15],"seen":[16],"large":[18],"body":[19],"of":[20,39,46,49,83,113,222,244],"work":[21],"on":[22,36,52,199],"detecting":[23],"changes":[24],"and":[25,43,71,76,133,152,201],"building":[26],"prediction":[27],"models":[28],"from":[29,173],"stream":[30],"data,":[31],"with":[32],"vague":[34],"understanding":[35],"the":[37,40,44,53,111,114,118,166,174,194,213,220,223,228,235,242,245],"types":[38,48],"impact":[45],"different":[47],"algorithms.":[55],"In":[56],"this":[57],"paper,":[58],"we":[59,102,155],"first":[60],"categorize":[61],"into":[64],"two":[65],"scenarios:":[66],"Loose":[67],"Concept":[68,73],"Drifting":[69,74],"(LCD)":[70],"Rigorous":[72],"(RCD),":[75],"then":[77],"propose":[78,156],"solutions":[79],"to":[80,99,109,129,164,190],"handle":[81,134],"each":[82,100],"them":[84],"separately.":[85],"For":[86,139],"LCD":[87],"streams,":[89,142],"because":[90,143],"concepts":[91,145],"in":[92,117,146,193],"adjacent":[93,147],"chunks":[95,116,149],"are":[96],"sufficiently":[97],"close":[98],"other,":[101],"apply":[103],"kernel":[104,119],"mean":[105],"matching":[106],"(KMM)":[107],"method":[108,163],"minimize":[110],"discrepancy":[112],"space.":[120],"Such":[121],"minimization":[123],"process":[124],"will":[125,204],"produce":[126],"weighted":[127,207,229],"instances":[128,192],"build":[130],"classifier":[131,188,230],"ensemble":[132,189],"streams.":[138],"RCD":[140],"genuine":[144],"may":[150],"randomly":[151],"rapidly":[153],"change,":[154],"new":[158],"Optimal":[159],"Weights":[160],"Adjustment":[161],"(OWA)":[162],"determine":[165],"optimum":[167],"weight":[168],"values":[169],"classifiers":[171,183],"trained":[172],"most":[175],"recent":[176],"(up-to-date)":[177],"chunk,":[179],"such":[180],"that":[181,206],"those":[182],"can":[184],"form":[185],"an":[186],"accurate":[187],"predict":[191],"yet-to-come":[195],"chunk.":[197],"Experiments":[198],"synthetic":[200],"real-world":[202],"datasets":[203],"show":[205],"instance":[208],"approach":[209,231],"preferable":[211,233],"when":[212,234],"mainly":[217,239],"caused":[218],"by":[219,241],"changing":[221,243],"class":[224],"prior":[225],"probability;":[226],"whereas":[227],"triggered":[240],"conditional":[246],"probability.":[247]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":12},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":8}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
