{"id":"https://openalex.org/W4200427624","doi":"https://doi.org/10.1109/tnnls.2021.3132584","title":"OSNN: An Online Semisupervised Neural Network for Nonstationary Data Streams","display_name":"OSNN: An Online Semisupervised Neural Network for Nonstationary Data Streams","publication_year":2021,"publication_date":"2021-12-21","ids":{"openalex":"https://openalex.org/W4200427624","doi":"https://doi.org/10.1109/tnnls.2021.3132584","pmid":"https://pubmed.ncbi.nlm.nih.gov/34932489"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2021.3132584","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3132584","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://research.birmingham.ac.uk/en/publications/99f47b61-95a6-46a0-a4d6-2d8eee50eeed","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087346190","display_name":"Rodrigo G. F. Soares","orcid":"https://orcid.org/0000-0003-4806-3652"},"institutions":[{"id":"https://openalex.org/I62921916","display_name":"Universidade Federal Rural de Pernambuco","ror":"https://ror.org/02ksmb993","country_code":"BR","type":"education","lineage":["https://openalex.org/I62921916"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Rodrigo G. F. Soares","raw_affiliation_strings":["Department of Statistics and Informatics, Federal Rural University of Pernambuco, Recife, Brazil"],"raw_orcid":"https://orcid.org/0000-0003-4806-3652","affiliations":[{"raw_affiliation_string":"Department of Statistics and Informatics, Federal Rural University of Pernambuco, Recife, Brazil","institution_ids":["https://openalex.org/I62921916"]}]},{"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, The University of Birmingham, Birmingham, U.K"],"raw_orcid":"https://orcid.org/0000-0002-2639-0671","affiliations":[{"raw_affiliation_string":"School of Computer Science, The University of Birmingham, Birmingham, U.K","institution_ids":["https://openalex.org/I79619799"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9102,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.80273902,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"34","issue":"9","first_page":"6029","last_page":"6041"},"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":0.988099992275238,"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":0.9815000295639038,"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/exploit","display_name":"Exploit","score":0.8549633026123047},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8050522804260254},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.731285572052002},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6468977928161621},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6209139227867126},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5861497521400452},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5692133903503418},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.526349663734436},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5209911465644836},{"id":"https://openalex.org/keywords/learning-vector-quantization","display_name":"Learning vector quantization","score":0.4902832806110382},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4274994134902954}],"concepts":[{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.8549633026123047},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8050522804260254},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.731285572052002},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6468977928161621},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6209139227867126},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5861497521400452},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5692133903503418},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.526349663734436},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5209911465644836},{"id":"https://openalex.org/C40567965","wikidata":"https://www.wikidata.org/wiki/Q1820283","display_name":"Learning vector quantization","level":3,"score":0.4902832806110382},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4274994134902954},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tnnls.2021.3132584","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3132584","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:34932489","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34932489","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/99f47b61-95a6-46a0-a4d6-2d8eee50eeed","is_oa":true,"landing_page_url":"https://research.birmingham.ac.uk/en/publications/99f47b61-95a6-46a0-a4d6-2d8eee50eeed","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":"Soares, R & Minku, L 2021, 'OSNN : an online semisupervised neural network for nonstationary data streams', IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/TNNLS.2021.3132584","raw_type":"article"},{"id":"pmh:oai:pure.atira.dk:publications/99f47b61-95a6-46a0-a4d6-2d8eee50eeed","is_oa":false,"landing_page_url":"https://birmingham.elsevierpure.com/en/publications/99f47b61-95a6-46a0-a4d6-2d8eee50eeed","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":""}],"best_oa_location":{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/99f47b61-95a6-46a0-a4d6-2d8eee50eeed","is_oa":true,"landing_page_url":"https://research.birmingham.ac.uk/en/publications/99f47b61-95a6-46a0-a4d6-2d8eee50eeed","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":"Soares, R & Minku, L 2021, 'OSNN : an online semisupervised neural network for nonstationary data streams', IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/TNNLS.2021.3132584","raw_type":"article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G438649878","display_name":"Experience-based Computation: Learning to Optimise","funder_award_id":"766186","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G4781280766","display_name":null,"funder_award_id":"EP/R006660/2","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G6192470683","display_name":"Stable Prediction of Defect-Inducing Software Changes (SPDISC)","funder_award_id":"EP/R006660/2","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G781164028","display_name":null,"funder_award_id":"R006660/2","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W265189144","https://openalex.org/W1479807131","https://openalex.org/W1509543116","https://openalex.org/W1565746575","https://openalex.org/W1585854823","https://openalex.org/W1603138887","https://openalex.org/W1904826605","https://openalex.org/W1963581687","https://openalex.org/W1969811075","https://openalex.org/W1990079212","https://openalex.org/W1990863955","https://openalex.org/W2009155043","https://openalex.org/W2044574055","https://openalex.org/W2058090194","https://openalex.org/W2063941608","https://openalex.org/W2068714596","https://openalex.org/W2073256825","https://openalex.org/W2097998348","https://openalex.org/W2099419573","https://openalex.org/W2100406636","https://openalex.org/W2115677675","https://openalex.org/W2116119284","https://openalex.org/W2123003172","https://openalex.org/W2126510745","https://openalex.org/W2131246644","https://openalex.org/W2154455818","https://openalex.org/W2162647716","https://openalex.org/W2252617635","https://openalex.org/W2470412537","https://openalex.org/W2521291598","https://openalex.org/W2793402332","https://openalex.org/W2803971899","https://openalex.org/W2896176775","https://openalex.org/W2897349693","https://openalex.org/W2901287800","https://openalex.org/W2963451778","https://openalex.org/W2997701990","https://openalex.org/W3007134847","https://openalex.org/W3011524553","https://openalex.org/W3115143688","https://openalex.org/W4212863985","https://openalex.org/W4241336979","https://openalex.org/W6633070339","https://openalex.org/W6635179022","https://openalex.org/W6674385629","https://openalex.org/W6675747103","https://openalex.org/W6682494755","https://openalex.org/W6751453669","https://openalex.org/W6788198723"],"related_works":["https://openalex.org/W4389449520","https://openalex.org/W127192698","https://openalex.org/W2570600173","https://openalex.org/W2893008024","https://openalex.org/W2743735673","https://openalex.org/W2360131081","https://openalex.org/W2985941356","https://openalex.org/W2802243998","https://openalex.org/W2137094200","https://openalex.org/W1521014365"],"abstract_inverted_index":{"Learning":[0],"from":[1,6],"data":[2,32,45,62,106,130,157,163],"streams":[3,164],"that":[4,132,151],"emerge":[5],"nonstationary":[7],"environments":[8],"has":[9],"many":[10],"real-world":[11],"applications":[12],"and":[13,31,85,127],"poses":[14],"various":[15],"challenges.":[16],"A":[17],"key":[18],"characteristic":[19],"of":[20,28,162],"such":[21,69],"a":[22,59,74,116],"task":[23],"is":[24,64,90],"the":[25,145],"varying":[26],"nature":[27],"target":[29],"functions":[30],"distributions":[33],"over":[34,134],"time":[35],"(concept":[36],"drifts).":[37],"Most":[38],"existing":[39],"work":[40],"relies":[41],"solely":[42],"on":[43,140],"labeled":[44],"to":[46,48,77,103,123,143,158,172],"adapt":[47],"concept":[49,109,173],"drifts":[50,110],"in":[51,58,111],"classification":[52,112],"problems.":[53,113],"However,":[54],"labeling":[55],"all":[56],"instances":[57],"potentially":[60],"life-long":[61],"stream":[63],"frequently":[65],"prohibitively":[66],"expensive,":[67],"hindering":[68],"approaches.":[70],"Therefore,":[71],"we":[72],"propose":[73],"novel":[75,117],"algorithm":[76,89],"exploit":[78,104],"unlabeled":[79,105,156],"instances,":[80],"which":[81],"are":[82],"typically":[83],"plentiful":[84],"easily":[86],"obtained.":[87],"The":[88],"an":[91],"online":[92],"semisupervised":[93,118],"radial":[94],"basis":[95],"function":[96],"neural":[97],"network":[98,125,146],"(OSNN)":[99],"with":[100],"manifold-based":[101],"training":[102],"while":[107,165],"tackling":[108],"OSNN":[114,152],"employs":[115],"learning":[119,139,169],"vector":[120],"quantization":[121],"(SLVQ)":[122],"train":[124],"centers":[126],"learn":[128],"meaningful":[129],"representations":[131],"change":[133],"time.":[135],"It":[136],"uses":[137],"manifold":[138],"dynamic":[141,167],"graphs":[142],"adjust":[144],"weights.":[147],"Our":[148],"experiments":[149],"confirm":[150],"can":[153],"effectively":[154],"use":[155],"elucidate":[159],"underlying":[160],"structures":[161],"its":[166],"topology":[168],"provides":[170],"robustness":[171],"drifts.":[174]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-20T07:56:41.581041","created_date":"2025-10-10T00:00:00"}