{"id":"https://openalex.org/W4207027909","doi":"https://doi.org/10.1093/jigpal/jzac033","title":"Data streams classification using deep learning under different speeds and drifts","display_name":"Data streams classification using deep learning under different speeds and drifts","publication_year":2022,"publication_date":"2022-01-24","ids":{"openalex":"https://openalex.org/W4207027909","doi":"https://doi.org/10.1093/jigpal/jzac033"},"language":"en","primary_location":{"id":"doi:10.1093/jigpal/jzac033","is_oa":true,"landing_page_url":"https://doi.org/10.1093/jigpal/jzac033","pdf_url":"https://academic.oup.com/jigpal/advance-article-pdf/doi/10.1093/jigpal/jzac033/42901449/jzac033.pdf","source":{"id":"https://openalex.org/S2734381524","display_name":"Logic Journal of IGPL","issn_l":"1367-0751","issn":["1367-0751","1368-9894"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Logic Journal of the IGPL","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://academic.oup.com/jigpal/advance-article-pdf/doi/10.1093/jigpal/jzac033/42901449/jzac033.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070105516","display_name":"Pedro Lara-Ben\u00edtez","orcid":"https://orcid.org/0000-0003-0457-8099"},"institutions":[{"id":"https://openalex.org/I79238269","display_name":"Universidad de Sevilla","ror":"https://ror.org/03yxnpp24","country_code":"ES","type":"education","lineage":["https://openalex.org/I79238269"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Pedro Lara-Ben\u00edtez","raw_affiliation_strings":["Division of Computer Science, University of Sevilla , ES-41012 Seville, Spain"],"affiliations":[{"raw_affiliation_string":"Division of Computer Science, University of Sevilla , ES-41012 Seville, Spain","institution_ids":["https://openalex.org/I79238269"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059940512","display_name":"Manuel Carranza-Garc\u00eda","orcid":"https://orcid.org/0000-0002-4729-8604"},"institutions":[{"id":"https://openalex.org/I79238269","display_name":"Universidad de Sevilla","ror":"https://ror.org/03yxnpp24","country_code":"ES","type":"education","lineage":["https://openalex.org/I79238269"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Manuel Carranza-Garc\u00eda","raw_affiliation_strings":["Division of Computer Science, University of Sevilla , ES-41012 Seville, Spain"],"affiliations":[{"raw_affiliation_string":"Division of Computer Science, University of Sevilla , ES-41012 Seville, Spain","institution_ids":["https://openalex.org/I79238269"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032952434","display_name":"David Guti\u00e9rrez\u2010Avil\u00e9s","orcid":"https://orcid.org/0000-0002-6292-9873"},"institutions":[{"id":"https://openalex.org/I79238269","display_name":"Universidad de Sevilla","ror":"https://ror.org/03yxnpp24","country_code":"ES","type":"education","lineage":["https://openalex.org/I79238269"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"David Guti\u00e9rrez-Avil\u00e9s","raw_affiliation_strings":["Division of Computer Science, University of Sevilla , ES-41012 Seville, Spain"],"affiliations":[{"raw_affiliation_string":"Division of Computer Science, University of Sevilla , ES-41012 Seville, Spain","institution_ids":["https://openalex.org/I79238269"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036001529","display_name":"Jos\u00e9 C. Riquelme","orcid":"https://orcid.org/0000-0002-8243-2186"},"institutions":[{"id":"https://openalex.org/I79238269","display_name":"Universidad de Sevilla","ror":"https://ror.org/03yxnpp24","country_code":"ES","type":"education","lineage":["https://openalex.org/I79238269"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jos\u00e9 C Riquelme","raw_affiliation_strings":["Division of Computer Science, University of Sevilla , ES-41012 Seville, Spain"],"affiliations":[{"raw_affiliation_string":"Division of Computer Science, University of Sevilla , ES-41012 Seville, Spain","institution_ids":["https://openalex.org/I79238269"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5070105516"],"corresponding_institution_ids":["https://openalex.org/I79238269"],"apc_list":{"value":4151,"currency":"USD","value_usd":4151},"apc_paid":{"value":4151,"currency":"USD","value_usd":4151},"fwci":0.5553,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.70681571,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"31","issue":"4","first_page":"688","last_page":"700"},"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":0.9828000068664551,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9706000089645386,"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":0.8881601691246033},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.7377052903175354},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.6488238573074341},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6409095525741577},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.6057589650154114},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5996593832969666},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5802767872810364},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5479925274848938},{"id":"https://openalex.org/keywords/streaming-data","display_name":"Streaming data","score":0.4663727879524231},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46458700299263},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.4106101989746094},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3661620318889618},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3497931957244873}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8881601691246033},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.7377052903175354},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.6488238573074341},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6409095525741577},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.6057589650154114},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5996593832969666},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5802767872810364},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5479925274848938},{"id":"https://openalex.org/C2777611316","wikidata":"https://www.wikidata.org/wiki/Q39045282","display_name":"Streaming data","level":2,"score":0.4663727879524231},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46458700299263},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.4106101989746094},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3661620318889618},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3497931957244873},{"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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:10.1093/jigpal/jzac033","is_oa":true,"landing_page_url":"https://doi.org/10.1093/jigpal/jzac033","pdf_url":"https://academic.oup.com/jigpal/advance-article-pdf/doi/10.1093/jigpal/jzac033/42901449/jzac033.pdf","source":{"id":"https://openalex.org/S2734381524","display_name":"Logic Journal of IGPL","issn_l":"1367-0751","issn":["1367-0751","1368-9894"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Logic Journal of the IGPL","raw_type":"journal-article"},{"id":"pmh:oai:idus.us.es:11441/130992","is_oa":true,"landing_page_url":"https://idus.us.es/handle//11441/130992","pdf_url":null,"source":{"id":"https://openalex.org/S4306400333","display_name":"idUS (Universidad de Sevilla)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79238269","host_organization_name":"Universidad de Sevilla","host_organization_lineage":["https://openalex.org/I79238269"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1093/jigpal/jzac033","is_oa":true,"landing_page_url":"https://doi.org/10.1093/jigpal/jzac033","pdf_url":"https://academic.oup.com/jigpal/advance-article-pdf/doi/10.1093/jigpal/jzac033/42901449/jzac033.pdf","source":{"id":"https://openalex.org/S2734381524","display_name":"Logic Journal of IGPL","issn_l":"1367-0751","issn":["1367-0751","1368-9894"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Logic Journal of the IGPL","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4207027909.pdf","grobid_xml":"https://content.openalex.org/works/W4207027909.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1525647652","https://openalex.org/W1988812547","https://openalex.org/W1992019053","https://openalex.org/W2073256825","https://openalex.org/W2136848157","https://openalex.org/W2626498001","https://openalex.org/W2747329762","https://openalex.org/W2888592368","https://openalex.org/W2898206393","https://openalex.org/W2912500072","https://openalex.org/W2962823293","https://openalex.org/W2977431930","https://openalex.org/W2988244882","https://openalex.org/W3000166127","https://openalex.org/W3107324520","https://openalex.org/W3109365969","https://openalex.org/W6684191040","https://openalex.org/W6696085341","https://openalex.org/W6755395053","https://openalex.org/W6755659550","https://openalex.org/W6768435821","https://openalex.org/W6787556164"],"related_works":["https://openalex.org/W4389449520","https://openalex.org/W4246591448","https://openalex.org/W2743735673","https://openalex.org/W2060628068","https://openalex.org/W2167004500","https://openalex.org/W3208495060","https://openalex.org/W1981058017","https://openalex.org/W2801575137","https://openalex.org/W2151831402","https://openalex.org/W2235038291"],"abstract_inverted_index":{"Abstract":[0],"Processing":[1],"data":[2,36,113,162],"streams":[3,142],"arriving":[4],"at":[5,143],"high":[6],"speed":[7],"requires":[8],"the":[9,25,57,70,76,89,104,151,184],"development":[10],"of":[11,59,75,84,98,106,109,177],"models":[12,64,121],"that":[13,43,138,168],"can":[14],"provide":[15],"fast":[16],"and":[17,87,128,179],"accurate":[18],"predictions.":[19],"Although":[20],"deep":[21,61],"neural":[22,131],"networks":[23,132],"are":[24,139,182],"state-of-the-art":[26],"for":[27,112],"many":[28],"machine":[29],"learning":[30,62],"tasks,":[31],"their":[32],"performance":[33,105,174],"in":[34,160,175],"real-time":[35],"streaming":[37,66,114],"scenarios":[38],"is":[39,101],"a":[40,172],"research":[41],"area":[42],"has":[44,53],"not":[45],"yet":[46],"been":[47,54],"fully":[48],"addressed.":[49],"Nevertheless,":[50],"much":[51],"effort":[52],"put":[55],"into":[56],"adaption":[58],"complex":[60],"(DL)":[63],"to":[65,102,155,187],"tasks":[67],"by":[68],"reducing":[69],"processing":[71],"time.":[72],"The":[73,96,164],"design":[74],"asynchronous":[77],"dual-pipeline":[78],"DL":[79,110],"framework":[80],"allows":[81],"making":[82],"predictions":[83],"incoming":[85],"instances":[86],"updating":[88],"model":[90],"simultaneously,":[91],"using":[92,116],"two":[93],"separate":[94],"layers.":[95],"aim":[97],"this":[99,117],"work":[100],"assess":[103],"different":[107,144,152],"types":[108],"architectures":[111,153,170],"classification":[115],"framework.":[118],"We":[119],"evaluate":[120,149],"such":[122],"as":[123,141],"multi-layer":[124],"perceptrons,":[125],"recurrent,":[126],"convolutional":[127,130,169],"temporal":[129],"over":[133],"several":[134],"time":[135],"series":[136],"datasets":[137],"simulated":[140],"speeds.":[145],"In":[146],"addition,":[147],"we":[148],"how":[150],"react":[154],"concept":[156,188],"drifts":[157],"typically":[158],"found":[159],"evolving":[161],"streams.":[163],"obtained":[165],"results":[166],"indicate":[167],"achieve":[171],"higher":[173],"terms":[176],"accuracy":[178],"efficiency,":[180],"but":[181],"also":[183],"most":[185],"sensitive":[186],"drifts.":[189]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}