{"id":"https://openalex.org/W2896367187","doi":"https://doi.org/10.1109/ijcnn.2018.8489049","title":"Adaptive Incremental Gaussian Mixture Network for Non-Stationary Data Stream Classification","display_name":"Adaptive Incremental Gaussian Mixture Network for Non-Stationary Data Stream Classification","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2896367187","doi":"https://doi.org/10.1109/ijcnn.2018.8489049","mag":"2896367187"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2018.8489049","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8489049","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5035570562","display_name":"Jorge C. Chamby-Diaz","orcid":"https://orcid.org/0000-0001-6765-2650"},"institutions":[{"id":"https://openalex.org/I130442723","display_name":"Universidade Federal do Rio Grande do Sul","ror":"https://ror.org/041yk2d64","country_code":"BR","type":"education","lineage":["https://openalex.org/I130442723"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Jorge  C. Chamby-Diaz","raw_affiliation_strings":["Institute of Informatics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Informatics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil","institution_ids":["https://openalex.org/I130442723"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039060913","display_name":"Mariana Recamonde\u2010Mendoza","orcid":"https://orcid.org/0000-0003-2800-1032"},"institutions":[{"id":"https://openalex.org/I130442723","display_name":"Universidade Federal do Rio Grande do Sul","ror":"https://ror.org/041yk2d64","country_code":"BR","type":"education","lineage":["https://openalex.org/I130442723"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Mariana Recamonde-Mendoza","raw_affiliation_strings":["Institute of Informatics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Informatics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil","institution_ids":["https://openalex.org/I130442723"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028225369","display_name":"Ana L. C. Bazzan","orcid":"https://orcid.org/0000-0002-2803-9607"},"institutions":[{"id":"https://openalex.org/I130442723","display_name":"Universidade Federal do Rio Grande do Sul","ror":"https://ror.org/041yk2d64","country_code":"BR","type":"education","lineage":["https://openalex.org/I130442723"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Ana L. C. Bazzan","raw_affiliation_strings":["Institute of Informatics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Informatics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil","institution_ids":["https://openalex.org/I130442723"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027755211","display_name":"Ricardo Grunitzki","orcid":null},"institutions":[{"id":"https://openalex.org/I130442723","display_name":"Universidade Federal do Rio Grande do Sul","ror":"https://ror.org/041yk2d64","country_code":"BR","type":"education","lineage":["https://openalex.org/I130442723"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Ricardo Grunitzki","raw_affiliation_strings":["Institute of Informatics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Informatics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil","institution_ids":["https://openalex.org/I130442723"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130442723"],"apc_list":null,"apc_paid":null,"fwci":0.1132,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.41118916,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"5772","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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9602000117301941,"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"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9315999746322632,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/concept-drift","display_name":"Concept drift","score":0.859296441078186},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7664247751235962},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.6195951104164124},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.5597335696220398},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5553756356239319},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5353226065635681},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5102636814117432},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5029067397117615},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4891958236694336},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.445991575717926},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.43587902188301086},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.4200867712497711},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.41062378883361816},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.39196494221687317},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35587000846862793}],"concepts":[{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.859296441078186},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7664247751235962},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.6195951104164124},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.5597335696220398},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5553756356239319},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5353226065635681},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5102636814117432},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5029067397117615},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4891958236694336},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.445991575717926},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.43587902188301086},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4200867712497711},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.41062378883361816},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.39196494221687317},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35587000846862793},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2018.8489049","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8489049","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W27170557","https://openalex.org/W108703714","https://openalex.org/W1525647652","https://openalex.org/W1585854823","https://openalex.org/W1619452145","https://openalex.org/W1770825568","https://openalex.org/W1977640460","https://openalex.org/W1992019053","https://openalex.org/W1994616650","https://openalex.org/W2060277733","https://openalex.org/W2069701377","https://openalex.org/W2083121989","https://openalex.org/W2102387656","https://openalex.org/W2115677675","https://openalex.org/W2127757685","https://openalex.org/W2135335717","https://openalex.org/W2135346934","https://openalex.org/W2160512933","https://openalex.org/W2171809276","https://openalex.org/W2252617635","https://openalex.org/W2254648979","https://openalex.org/W2296276442","https://openalex.org/W2528421823","https://openalex.org/W2602516395","https://openalex.org/W3003253354","https://openalex.org/W3082998439","https://openalex.org/W3110683067","https://openalex.org/W3120740533","https://openalex.org/W4285719527","https://openalex.org/W6680192438","https://openalex.org/W6685747873","https://openalex.org/W6691736701","https://openalex.org/W6727866626","https://openalex.org/W6786768871"],"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":{"Data":[0],"stream":[1],"classification":[2,133,180],"poses":[3],"many":[4],"challenges":[5],"for":[6,132,152,179],"the":[7,12,20,26,93,102,108,161,173,202,206,213],"data":[8,84,142,199],"mining":[9],"community":[10],"when":[11],"environment":[13],"is":[14,29,88,146,157],"non-stationary,":[15],"among":[16],"which":[17,56],"adaptation":[18,96,159,183],"to":[19,36,53,63,91,172,184],"concept":[21,82,105,139,216],"drifts,":[22],"i.e.,":[23],"changes":[24],"in":[25,101,113,141,170,189],"underlying":[27],"concepts,":[28],"a":[30,58,89,114,186],"major":[31],"one.":[32],"Two":[33],"main":[34,166],"ways":[35],"develop":[37],"adaptive":[38],"approaches":[39],"are":[40,67,175],"ensemble":[41,75,99],"methods":[42,47],"and":[43,69,95,129,156,182,197],"incremental":[44,118],"algorithms.":[45],"Ensemble":[46],"play":[48],"an":[49,98,126,135,158],"important":[50],"role":[51],"due":[52],"its":[54],"modularity,":[55],"provides":[57],"natural":[59],"way":[60],"of":[61,97,104,110,137,160,168,212,215],"adapting":[62],"change.":[64],"Incremental":[65,148],"algorithms":[66],"faster":[68],"have":[70,78],"better":[71],"anti-noise":[72],"capacity":[73],"than":[74],"algorithms,":[76],"but":[77],"more":[79],"restrictions":[80],"on":[81],"drifting":[83,140],"streams.":[85,143],"Thus,":[86],"it":[87],"challenge":[90],"combine":[92],"flexibility":[94],"classifier":[100,116],"presence":[103],"drift,":[106],"with":[107,117,194],"simplicity":[109],"use":[111],"found":[112],"single":[115],"learning.":[119],"With":[120],"this":[121,123],"motivation,":[122],"work":[124],"proposes":[125],"incremental,":[127],"online,":[128],"probabilistic":[130],"algorithm":[131,145],"as":[134],"effort":[136],"tackling":[138],"The":[144,164],"called":[147],"Gaussian":[149],"Mixture":[150],"Network":[151],"Non-Stationary":[153],"Environments":[154],"(IGMN-NSE)":[155],"IGMN":[162,174],"algorithm.":[163],"two":[165],"contributions":[167],"IGMN-NSE":[169,203],"relation":[171],"predictive":[176],"power":[177],"improvement":[178],"tasks":[181],"achieve":[185],"good":[187],"performance":[188],"non-stationary":[190],"environments.":[191],"Extensive":[192],"experiments":[193],"both":[195],"synthetic":[196],"real-world":[198],"demonstrate":[200],"that":[201],"can":[204],"track":[205],"changing":[207],"environments":[208],"very":[209],"closely,":[210],"regardless":[211],"type":[214],"drift.":[217]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}