{"id":"https://openalex.org/W4288039427","doi":"https://doi.org/10.1145/3551643","title":"Multiple Imputation Ensembles for Time Series (MIE-TS)","display_name":"Multiple Imputation Ensembles for Time Series (MIE-TS)","publication_year":2022,"publication_date":"2022-07-26","ids":{"openalex":"https://openalex.org/W4288039427","doi":"https://doi.org/10.1145/3551643"},"language":"en","primary_location":{"id":"doi:10.1145/3551643","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3551643","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://ueaeprints.uea.ac.uk/id/eprint/98272/1/3551643.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015515752","display_name":"Aliya Aleryani","orcid":"https://orcid.org/0000-0001-9844-0327"},"institutions":[{"id":"https://openalex.org/I1118541","display_name":"University of East Anglia","ror":"https://ror.org/026k5mg93","country_code":"GB","type":"education","lineage":["https://openalex.org/I1118541"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Aliya Aleryani","raw_affiliation_strings":["University of East Anglia, Norwich, Norfolk, UK"],"affiliations":[{"raw_affiliation_string":"University of East Anglia, Norwich, Norfolk, UK","institution_ids":["https://openalex.org/I1118541"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052459001","display_name":"Aaron Bostrom","orcid":"https://orcid.org/0000-0002-7300-6038"},"institutions":[{"id":"https://openalex.org/I1118541","display_name":"University of East Anglia","ror":"https://ror.org/026k5mg93","country_code":"GB","type":"education","lineage":["https://openalex.org/I1118541"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Aaron Bostrom","raw_affiliation_strings":["University of East Anglia, Norwich, Norfolk, UK"],"affiliations":[{"raw_affiliation_string":"University of East Anglia, Norwich, Norfolk, UK","institution_ids":["https://openalex.org/I1118541"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012776258","display_name":"Wenjia Wang","orcid":"https://orcid.org/0000-0001-9372-0418"},"institutions":[{"id":"https://openalex.org/I1118541","display_name":"University of East Anglia","ror":"https://ror.org/026k5mg93","country_code":"GB","type":"education","lineage":["https://openalex.org/I1118541"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Wenjia Wang","raw_affiliation_strings":["University of East Anglia, Norwich, Norfolk, UK"],"affiliations":[{"raw_affiliation_string":"University of East Anglia, Norwich, Norfolk, UK","institution_ids":["https://openalex.org/I1118541"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070947744","display_name":"Beatriz de la Iglesia","orcid":"https://orcid.org/0000-0003-2675-5826"},"institutions":[{"id":"https://openalex.org/I1118541","display_name":"University of East Anglia","ror":"https://ror.org/026k5mg93","country_code":"GB","type":"education","lineage":["https://openalex.org/I1118541"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Beatriz Iglesia","raw_affiliation_strings":["University of East Anglia, Norwich, Norfolk, UK"],"affiliations":[{"raw_affiliation_string":"University of East Anglia, Norwich, Norfolk, UK","institution_ids":["https://openalex.org/I1118541"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5015515752"],"corresponding_institution_ids":["https://openalex.org/I1118541"],"apc_list":null,"apc_paid":null,"fwci":1.0422,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.75191795,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"17","issue":"3","first_page":"1","last_page":"28"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":1.0,"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":0.9876999855041504,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9724000096321106,"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/imputation","display_name":"Imputation (statistics)","score":0.878797173500061},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.8297613263130188},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6353943347930908},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6054291129112244},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5421865582466125},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4912955164909363},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36759239435195923},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3510283827781677},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.34743356704711914},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3416028618812561},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2538526952266693}],"concepts":[{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.878797173500061},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.8297613263130188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6353943347930908},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6054291129112244},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5421865582466125},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4912955164909363},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36759239435195923},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3510283827781677},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.34743356704711914},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3416028618812561},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2538526952266693}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3551643","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3551643","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},{"id":"pmh:oai:ueaeprints.uea.ac.uk:98272","is_oa":true,"landing_page_url":null,"pdf_url":"https://ueaeprints.uea.ac.uk/id/eprint/98272/1/3551643.pdf","source":{"id":"https://openalex.org/S4306400384","display_name":"UEA Digital Repository (University of East Anglia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1118541","host_organization_name":"University of East Anglia","host_organization_lineage":["https://openalex.org/I1118541"],"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":"NonPeerReviewed"}],"best_oa_location":{"id":"pmh:oai:ueaeprints.uea.ac.uk:98272","is_oa":true,"landing_page_url":null,"pdf_url":"https://ueaeprints.uea.ac.uk/id/eprint/98272/1/3551643.pdf","source":{"id":"https://openalex.org/S4306400384","display_name":"UEA Digital Repository (University of East Anglia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1118541","host_organization_name":"University of East Anglia","host_organization_lineage":["https://openalex.org/I1118541"],"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":"NonPeerReviewed"},"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.6399999856948853}],"awards":[{"id":"https://openalex.org/G1219560291","display_name":null,"funder_award_id":"Economic","funder_id":"https://openalex.org/F4320334630","funder_display_name":"Economic and Social Research Council"},{"id":"https://openalex.org/G3482995644","display_name":"Smart Data Analytics for Business and Local Government","funder_award_id":"ES/L011859/1","funder_id":"https://openalex.org/F4320334630","funder_display_name":"Economic and Social Research Council"}],"funders":[{"id":"https://openalex.org/F4320334630","display_name":"Economic and Social Research Council","ror":"https://ror.org/03n0ht308"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4288039427.pdf","grobid_xml":"https://content.openalex.org/works/W4288039427.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W1583837637","https://openalex.org/W1730150177","https://openalex.org/W1822348759","https://openalex.org/W1853995153","https://openalex.org/W1968354112","https://openalex.org/W1973366456","https://openalex.org/W1984674851","https://openalex.org/W1985808723","https://openalex.org/W2028561976","https://openalex.org/W2049877533","https://openalex.org/W2064186732","https://openalex.org/W2085336722","https://openalex.org/W2091921805","https://openalex.org/W2107092366","https://openalex.org/W2108400301","https://openalex.org/W2111700774","https://openalex.org/W2123502857","https://openalex.org/W2125291718","https://openalex.org/W2128160875","https://openalex.org/W2132949918","https://openalex.org/W2147169507","https://openalex.org/W2147347448","https://openalex.org/W2150080215","https://openalex.org/W2151040995","https://openalex.org/W2156267802","https://openalex.org/W2165466912","https://openalex.org/W2166547175","https://openalex.org/W2171118759","https://openalex.org/W2313407065","https://openalex.org/W2555077524","https://openalex.org/W2581867724","https://openalex.org/W2591512686","https://openalex.org/W2604269166","https://openalex.org/W2752432857","https://openalex.org/W2754385338","https://openalex.org/W2801646001","https://openalex.org/W2888791883","https://openalex.org/W2898647012","https://openalex.org/W2911964244","https://openalex.org/W2926030578","https://openalex.org/W2944891321","https://openalex.org/W2954112873","https://openalex.org/W2964010366","https://openalex.org/W3005285192","https://openalex.org/W3010158807","https://openalex.org/W3018026180","https://openalex.org/W3098967488","https://openalex.org/W3101942798","https://openalex.org/W3115948762","https://openalex.org/W4289360400","https://openalex.org/W4298826872","https://openalex.org/W4399576149","https://openalex.org/W6870010312","https://openalex.org/W7011406682"],"related_works":["https://openalex.org/W3150051843","https://openalex.org/W2541565311","https://openalex.org/W3049453136","https://openalex.org/W2784019465","https://openalex.org/W2943291682","https://openalex.org/W3021292873","https://openalex.org/W2751555317","https://openalex.org/W2096555119","https://openalex.org/W2159586267","https://openalex.org/W3082860126"],"abstract_inverted_index":{"Time":[0,21,181],"series":[1,22,87,161,191],"classification":[2,155],"has":[3,241],"become":[4],"an":[5,50],"interesting":[6],"field":[7],"of":[8,36,73,199,207,210],"research,":[9],"thanks":[10],"to":[11,144],"the":[12,17,31,75,197,205,208,218,222,235,249],"extensive":[13],"studies":[14],"conducted":[15],"in":[16,71,78,85,213],"past":[18],"two":[19,94],"decades.":[20],"may":[23,28,232],"have":[24],"missing":[25,41,79,123,228],"data,":[26,224],"which":[27,252],"affect":[29],"both":[30],"representation":[32],"and":[33,117,147,175,185,202,245],"also":[34],"modeling":[35],"time":[37,45,86,99,160,190],"series.":[38,100],"Thus,":[39],"recovering":[40],"data":[42,57,141,229],"using":[43,153],"appropriate":[44],"series-based":[46],"imputation":[47,54,96,106,116,137,201,240],"methods":[48],"is":[49,55,83,103,113,253],"essential":[51],"step.":[52],"Multiple":[53],"a":[56,104,114,127,242,254],"recovery":[58],"method":[59,67,107],"where":[60],"it":[61,82],"produced":[62],"multiple":[63,95,105,115,200,239],"imputed":[64,140],"data.":[65],"The":[66,101,111,139,163],"proves":[68],"its":[69],"usefulness":[70],"terms":[72],"reflecting":[74],"uncertainty":[76],"inherit":[77],"data;":[80],"however,":[81],"under-researched":[84],"problems.":[88],"In":[89],"this":[90,214],"article,":[91],"we":[92,121,134],"propose":[93],"approaches":[97],"for":[98],"first":[102],"based":[108],"on":[109,248],"interpolation.":[110],"second":[112],"ensemble":[118,203],"method.":[119],"First,":[120],"simulate":[122],"consecutive":[124],"sub-sequences":[125],"under":[126,226],"Missing":[128],"Completely":[129],"at":[130],"Random":[131,167],"mechanism;":[132],"then,":[133],"use":[135],"single/multiple":[136],"methods.":[138],"are":[142,187],"used":[143],"build":[145,151],"bagging":[146],"stacking":[148],"ensembles.":[149],"We":[150],"ensembles":[152],"standard":[154,164],"algorithms":[156],"as":[157,159,189],"well":[158],"classifiers.":[162,192],"classifiers":[165,211],"involve":[166],"Forest,":[168,180,183],"Support":[169],"Vector":[170],"Machines,":[171],"K-Nearest":[172],"Neighbour,":[173],"C4.5,":[174],"PART":[176],"while":[177],"TSCHIEF,":[178],"Proximity":[179],"Series":[182],"RISE,":[184],"BOSS":[186],"chosen":[188],"Our":[193],"findings":[194],"show":[195],"that":[196],"combination":[198],"improves":[204],"performance":[206,219],"majority":[209],"tested":[212],"study,":[215],"often":[216],"above":[217],"obtained":[220],"from":[221],"complete":[223],"even":[225],"increasing":[227],"scenarios.":[230],"This":[231],"be":[233],"because":[234],"diversity":[236],"injected":[237],"by":[238],"very":[243,255],"favourable":[244],"stabilising":[246],"effect":[247],"classifier":[250],"performance,":[251],"important":[256],"finding.":[257]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}