{"id":"https://openalex.org/W2607420770","doi":"https://doi.org/10.1080/00401706.2017.1317291","title":"A Nonparametric Adaptive Sampling Strategy for Online Monitoring of Big Data Streams","display_name":"A Nonparametric Adaptive Sampling Strategy for Online Monitoring of Big Data Streams","publication_year":2017,"publication_date":"2017-04-10","ids":{"openalex":"https://openalex.org/W2607420770","doi":"https://doi.org/10.1080/00401706.2017.1317291","mag":"2607420770"},"language":"en","primary_location":{"id":"doi:10.1080/00401706.2017.1317291","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00401706.2017.1317291","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-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/A5030183256","display_name":"Xiaochen Xian","orcid":"https://orcid.org/0000-0001-7099-2488"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaochen Xian","raw_affiliation_strings":["Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100665239","display_name":"Andi Wang","orcid":"https://orcid.org/0000-0003-4925-1962"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Andi Wang","raw_affiliation_strings":["Department of Industrial Engineering and Logistics Management, Hong Kong University of Science and Technology, Clear Waterbay, NT, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering and Logistics Management, Hong Kong University of Science and Technology, Clear Waterbay, NT, Hong Kong","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025012113","display_name":"Kaibo Liu","orcid":"https://orcid.org/0000-0003-2863-5748"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kaibo Liu","raw_affiliation_strings":["Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI","institution_ids":["https://openalex.org/I135310074"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5025012113"],"corresponding_institution_ids":["https://openalex.org/I135310074"],"apc_list":null,"apc_paid":null,"fwci":3.1655,"has_fulltext":false,"cited_by_count":61,"citation_normalized_percentile":{"value":0.92214045,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"60","issue":"1","first_page":"14","last_page":"25"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9837999939918518,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/computer-science","display_name":"Computer science","score":0.7969900369644165},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.7353847026824951},{"id":"https://openalex.org/keywords/cusum","display_name":"CUSUM","score":0.712554931640625},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6757382750511169},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.6238196492195129},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6064783930778503},{"id":"https://openalex.org/keywords/adaptive-sampling","display_name":"Adaptive sampling","score":0.5956345200538635},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5676466226577759},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5348576307296753},{"id":"https://openalex.org/keywords/statistical-process-control","display_name":"Statistical process control","score":0.4692784547805786},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4661577641963959},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.45391470193862915},{"id":"https://openalex.org/keywords/concept-drift","display_name":"Concept drift","score":0.4148636758327484},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.17721882462501526},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16795024275779724},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.14640694856643677},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09229779243469238}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7969900369644165},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.7353847026824951},{"id":"https://openalex.org/C178518018","wikidata":"https://www.wikidata.org/wiki/Q1024555","display_name":"CUSUM","level":2,"score":0.712554931640625},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6757382750511169},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.6238196492195129},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6064783930778503},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.5956345200538635},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5676466226577759},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5348576307296753},{"id":"https://openalex.org/C113644684","wikidata":"https://www.wikidata.org/wiki/Q1356717","display_name":"Statistical process control","level":3,"score":0.4692784547805786},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4661577641963959},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.45391470193862915},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.4148636758327484},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.17721882462501526},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16795024275779724},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.14640694856643677},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09229779243469238},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/00401706.2017.1317291","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00401706.2017.1317291","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Technometrics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.47999998927116394,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G4221630706","display_name":null,"funder_award_id":"NSF CMMI-1362529","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337391","display_name":"Division of Civil, Mechanical and Manufacturing Innovation","ror":"https://ror.org/028yd4c30"},{"id":"https://openalex.org/F4320338287","display_name":"Oak Ridge National Laboratory","ror":"https://ror.org/01qz5mb56"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W29405787","https://openalex.org/W55601486","https://openalex.org/W60739391","https://openalex.org/W1664431191","https://openalex.org/W1969474438","https://openalex.org/W1971084072","https://openalex.org/W1973741119","https://openalex.org/W1975061413","https://openalex.org/W1984605331","https://openalex.org/W1988725147","https://openalex.org/W1999971199","https://openalex.org/W2008668719","https://openalex.org/W2018897326","https://openalex.org/W2019110314","https://openalex.org/W2030271755","https://openalex.org/W2038869097","https://openalex.org/W2045067839","https://openalex.org/W2047867619","https://openalex.org/W2053768275","https://openalex.org/W2061198552","https://openalex.org/W2062180331","https://openalex.org/W2074013991","https://openalex.org/W2093401273","https://openalex.org/W2097955094","https://openalex.org/W2102182691","https://openalex.org/W2103912032","https://openalex.org/W2106632614","https://openalex.org/W2114189440","https://openalex.org/W2114402558","https://openalex.org/W2131167729","https://openalex.org/W2145058161","https://openalex.org/W2157202423","https://openalex.org/W2158142902","https://openalex.org/W2293302691","https://openalex.org/W3103729929","https://openalex.org/W3105702803","https://openalex.org/W4231456352","https://openalex.org/W4240466294","https://openalex.org/W4242631541","https://openalex.org/W4244024201","https://openalex.org/W6836436062"],"related_works":["https://openalex.org/W2802243998","https://openalex.org/W2469699777","https://openalex.org/W3112950814","https://openalex.org/W3201554469","https://openalex.org/W2368264659","https://openalex.org/W4307392573","https://openalex.org/W2060628068","https://openalex.org/W4200217704","https://openalex.org/W2070787438","https://openalex.org/W2161835057"],"abstract_inverted_index":{"With":[0],"the":[1,47,80,110,114,121,144,147],"rapid":[2],"advancement":[3],"of":[4,10,49,56,93,113,128,146],"sensor":[5],"technology,":[6],"a":[7,33,54,70,90],"huge":[8],"amount":[9],"data":[11,44,98],"is":[12,123],"generated":[13],"in":[14,46,124],"various":[15],"applications,":[16],"which":[17,86],"poses":[18],"new":[19],"and":[20,74,102,126,132,142],"unique":[21],"challenges":[22],"for":[23,152],"statistical":[24],"process":[25,122],"control":[26,125],"(SPC).":[27],"In":[28,64],"this":[29,66,153],"article,":[30],"we":[31],"propose":[32],"nonparametric":[34],"adaptive":[35],"sampling":[36,111],"(NAS)":[37],"strategy":[38],"to":[39,140],"online":[40],"monitor":[41],"nonnormal":[42],"big":[43],"streams":[45,99],"context":[48],"limited":[50],"resources,":[51],"where":[52],"only":[53],"subset":[55],"observations":[57],"are":[58,100,118,135,155],"available":[59,156],"at":[60],"each":[61],"acquisition":[62],"time.":[63],"particular,":[65],"proposed":[67,115,148],"method":[68],"integrates":[69],"rank-based":[71],"CUSUM":[72],"scheme":[73],"an":[75],"innovative":[76],"idea":[77],"that":[78],"corrects":[79],"anti-rank":[81],"statistics":[82],"with":[83],"partial":[84],"observations,":[85],"can":[87],"effectively":[88],"detect":[89],"wide":[91],"range":[92],"possible":[94],"mean":[95],"shifts":[96],"when":[97,120],"exchangeable":[101],"follow":[103],"arbitrary":[104],"distributions.":[105],"Two":[106],"theoretical":[107],"properties":[108],"on":[109],"layout":[112],"NAS":[116],"algorithm":[117],"investigated":[119],"out":[127],"control.":[129],"Both":[130],"simulations":[131],"case":[133],"studies":[134],"conducted":[136],"under":[137],"different":[138],"scenarios":[139],"illustrate":[141],"evaluate":[143],"performance":[145],"method.":[149],"Supplementary":[150],"materials":[151],"article":[154],"online.":[157]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":4}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}
