{"id":"https://openalex.org/W4206357462","doi":"https://doi.org/10.1109/bigdata52589.2021.9671365","title":"Kalman Filtering for Learning with Evolving Data Streams","display_name":"Kalman Filtering for Learning with Evolving Data Streams","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4206357462","doi":"https://doi.org/10.1109/bigdata52589.2021.9671365"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9671365","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671365","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","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/A5022115251","display_name":"Giacomo Ziffer","orcid":"https://orcid.org/0000-0002-2768-3580"},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Giacomo Ziffer","raw_affiliation_strings":["DEIB - Politecnico di Milano, Milano, Italy","POLIMI - Politecnico di Milano [Milan] (Piazza Leonardo da Vinci, 32 20133 Milano - Italy)"],"affiliations":[{"raw_affiliation_string":"DEIB - Politecnico di Milano, Milano, Italy","institution_ids":["https://openalex.org/I93860229"]},{"raw_affiliation_string":"POLIMI - Politecnico di Milano [Milan] (Piazza Leonardo da Vinci, 32 20133 Milano - Italy)","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087779654","display_name":"Alessio Bernardo","orcid":"https://orcid.org/0000-0002-3492-0345"},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alessio Bernardo","raw_affiliation_strings":["DEIB - Politecnico di Milano, Milano, Italy","POLIMI - Politecnico di Milano [Milan] (Piazza Leonardo da Vinci, 32 20133 Milano - Italy)"],"affiliations":[{"raw_affiliation_string":"DEIB - Politecnico di Milano, Milano, Italy","institution_ids":["https://openalex.org/I93860229"]},{"raw_affiliation_string":"POLIMI - Politecnico di Milano [Milan] (Piazza Leonardo da Vinci, 32 20133 Milano - Italy)","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015694017","display_name":"Emanuele Della Valle","orcid":"https://orcid.org/0000-0002-5176-5885"},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Emanuele Della Valle","raw_affiliation_strings":["DEIB - Politecnico di Milano, Milano, Italy","POLIMI - Politecnico di Milano [Milan] (Piazza Leonardo da Vinci, 32 20133 Milano - Italy)"],"affiliations":[{"raw_affiliation_string":"DEIB - Politecnico di Milano, Milano, Italy","institution_ids":["https://openalex.org/I93860229"]},{"raw_affiliation_string":"POLIMI - Politecnico di Milano [Milan] (Piazza Leonardo da Vinci, 32 20133 Milano - Italy)","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080970505","display_name":"Albert Bifet","orcid":"https://orcid.org/0000-0002-8339-7773"},"institutions":[{"id":"https://openalex.org/I12356871","display_name":"T\u00e9l\u00e9com Paris","ror":"https://ror.org/01naq7912","country_code":"FR","type":"education","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I52179390","display_name":"University of Waikato","ror":"https://ror.org/013fsnh78","country_code":"NZ","type":"education","lineage":["https://openalex.org/I52179390"]}],"countries":["FR","NZ"],"is_corresponding":false,"raw_author_name":"Albert Bifet","raw_affiliation_strings":["University of Waikato, Hamilton, New Zealand","INFRES - D\u00e9partement Informatique et R\u00e9seaux (46, rue Barrault \r\n75013 Paris - France)","DIG - Data, Intelligence and Graphs (T\u00e9l\u00e9com Paris 19 Place Marguerite Perey 91120 Palaiseau - France)"],"affiliations":[{"raw_affiliation_string":"University of Waikato, Hamilton, New Zealand","institution_ids":["https://openalex.org/I52179390"]},{"raw_affiliation_string":"INFRES - D\u00e9partement Informatique et R\u00e9seaux (46, rue Barrault \r\n75013 Paris - France)","institution_ids":[]},{"raw_affiliation_string":"DIG - Data, Intelligence and Graphs (T\u00e9l\u00e9com Paris 19 Place Marguerite Perey 91120 Palaiseau - France)","institution_ids":["https://openalex.org/I12356871"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5022115251"],"corresponding_institution_ids":["https://openalex.org/I93860229"],"apc_list":null,"apc_paid":null,"fwci":0.2513,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.52561226,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"5337","last_page":"5346"},"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9505000114440918,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9337000250816345,"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/data-stream-mining","display_name":"Data stream mining","score":0.8317083120346069},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8082345724105835},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.7787313461303711},{"id":"https://openalex.org/keywords/concept-drift","display_name":"Concept drift","score":0.7558509111404419},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.6500230431556702},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.6143802404403687},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4732133746147156},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4655272364616394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46200084686279297},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45780205726623535},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.4163326323032379}],"concepts":[{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.8317083120346069},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8082345724105835},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.7787313461303711},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.7558509111404419},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.6500230431556702},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.6143802404403687},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4732133746147156},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4655272364616394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46200084686279297},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45780205726623535},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.4163326323032379},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9671365","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671365","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-04468418v1","is_oa":false,"landing_page_url":"https://hal.science/hal-04468418","pdf_url":null,"source":{"id":"https://openalex.org/S4406922461","display_name":"SPIRE - Sciences Po Institutional REpository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data), Orlando, FL, USA, December 15-18, 2021, Dec 2021, Orlando (Floride, Etats-Unis) Virtuel, United States. pp.5337--5346, ⟨10.1109/BIGDATA52589.2021.9671365⟩","raw_type":"Conference papers"},{"id":"pmh:oai:re.public.polimi.it:11311/1202057","is_oa":false,"landing_page_url":"http://hdl.handle.net/11311/1202057","pdf_url":null,"source":{"id":"https://openalex.org/S4306400312","display_name":"Virtual Community of Pathological Anatomy (University of Castilla La Mancha)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79189158","host_organization_name":"University of Castilla-La Mancha","host_organization_lineage":["https://openalex.org/I79189158"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W27170557","https://openalex.org/W38774257","https://openalex.org/W121132053","https://openalex.org/W139044672","https://openalex.org/W1525647652","https://openalex.org/W1565746575","https://openalex.org/W1577823635","https://openalex.org/W1578276759","https://openalex.org/W1585854823","https://openalex.org/W1904826605","https://openalex.org/W1991076541","https://openalex.org/W1992019053","https://openalex.org/W2010657328","https://openalex.org/W2042961981","https://openalex.org/W2069701377","https://openalex.org/W2092832849","https://openalex.org/W2097178527","https://openalex.org/W2099419573","https://openalex.org/W2105934661","https://openalex.org/W2132277248","https://openalex.org/W2136233172","https://openalex.org/W2143991132","https://openalex.org/W2163731957","https://openalex.org/W2304640842","https://openalex.org/W2330820318","https://openalex.org/W2469405371","https://openalex.org/W2626498001","https://openalex.org/W2747747656","https://openalex.org/W2758219826","https://openalex.org/W2773951400","https://openalex.org/W2847284300","https://openalex.org/W2962774976","https://openalex.org/W3003253354","https://openalex.org/W4245276699","https://openalex.org/W6604878861","https://openalex.org/W6605683200","https://openalex.org/W6633774736","https://openalex.org/W6680192438","https://openalex.org/W6752866118"],"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":{"Processing":[0],"data":[1,65,71,90],"streams":[2],"gained":[3],"much":[4],"importance":[5],"in":[6],"recent":[7],"years.":[8],"Standard":[9],"machine":[10],"learning":[11,99],"algorithms":[12,32],"do":[13],"not":[14],"cope":[15],"well":[16],"with":[17,126],"non-stationary":[18],"streaming":[19],"data,":[20],"where":[21],"decision":[22],"models":[23],"evolve":[24],"and":[25,41,74,102,141,159,162],"generate":[26],"so-called":[27],"concept":[28,50,75,139,147],"drift.":[29,51],"Online":[30],"adaptive":[31],"emerged":[33],"to":[34,47,49,62,144],"solve":[35],"these":[36],"issues.":[37],"They":[38],"learn":[39],"incrementally":[40],"generally":[42],"require":[43],"explicit":[44],"forgetting":[45],"mechanisms":[46],"adapt":[48],"In":[52],"this":[53],"paper,":[54],"we":[55,93,114],"propose":[56,115],"the":[57,89,107,116,123,132,145,151],"application":[58],"of":[59,122],"Kalman":[60,96,118,133],"filtering":[61],"handle":[63],"evolving":[64],"streams.":[66,91],"This":[67],"novel":[68],"approach":[69,136,161],"addresses":[70],"stream":[72],"mining":[73],"drift":[76],"management":[77],"challenges":[78],"from":[79],"a":[80,85,95,100,120],"new":[81],"perspective,":[82],"directly":[83],"modelling":[84],"representation":[86],"suitable":[87],"for":[88],"First,":[92],"study":[94],"filter":[97,134],"based":[98,135],"pproach":[101],"investigate":[103],"its":[104],"integration":[105],"into":[106],"Na\u00efve":[108],"Bayes":[109],"algorithm,":[110],"namely":[111],"KalmanNB.":[112,127],"Additionally,":[113],"Hoeffding":[117,124],"Tree,":[119],"combination":[121],"Tree":[125],"Empirical":[128],"results":[129],"demonstrate":[130],"that":[131],"inherently":[137],"manages":[138],"drifts,":[140],"it":[142,155],"adapts":[143],"emerging":[146],"more":[148],"rapidly":[149],"than":[150],"state-of-the-art":[152],"algorithms.":[153],"Moreover,":[154],"is":[156],"an":[157],"accurate":[158],"robust":[160],"requires":[163],"less":[164],"storage":[165],"while":[166],"still":[167],"being":[168],"faster.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}