{"id":"https://openalex.org/W4366728284","doi":"https://doi.org/10.48550/arxiv.2304.09182","title":"A Deep Learning Framework for Traffic Data Imputation Considering Spatiotemporal Dependencies","display_name":"A Deep Learning Framework for Traffic Data Imputation Considering Spatiotemporal Dependencies","publication_year":2023,"publication_date":"2023-04-18","ids":{"openalex":"https://openalex.org/W4366728284","doi":"https://doi.org/10.48550/arxiv.2304.09182"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2304.09182","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2304.09182","pdf_url":"https://arxiv.org/pdf/2304.09182","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2304.09182","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100392397","display_name":"Jiang Li","orcid":"https://orcid.org/0009-0009-7959-4019"},"institutions":[{"id":"https://openalex.org/I3018882396","display_name":"Victor (Japan)","ror":"https://ror.org/04b0q3m21","country_code":"JP","type":"company","lineage":["https://openalex.org/I3018882396"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Jiang, Li","raw_affiliation_strings":["Victor"],"affiliations":[{"raw_affiliation_string":"Victor","institution_ids":["https://openalex.org/I3018882396"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100458347","display_name":"Ting Zhang","orcid":"https://orcid.org/0000-0003-0099-9670"},"institutions":[{"id":"https://openalex.org/I3018882396","display_name":"Victor (Japan)","ror":"https://ror.org/04b0q3m21","country_code":"JP","type":"company","lineage":["https://openalex.org/I3018882396"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zhang, Ting","raw_affiliation_strings":["Victor"],"affiliations":[{"raw_affiliation_string":"Victor","institution_ids":["https://openalex.org/I3018882396"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026779201","display_name":"Qiruyi Zuo","orcid":"https://orcid.org/0000-0001-7363-0685"},"institutions":[{"id":"https://openalex.org/I3018882396","display_name":"Victor (Japan)","ror":"https://ror.org/04b0q3m21","country_code":"JP","type":"company","lineage":["https://openalex.org/I3018882396"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zuo, Qiruyi","raw_affiliation_strings":["Victor"],"affiliations":[{"raw_affiliation_string":"Victor","institution_ids":["https://openalex.org/I3018882396"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110967578","display_name":"Chenyu Tian","orcid":"https://orcid.org/0009-0005-8798-0826"},"institutions":[{"id":"https://openalex.org/I3018882396","display_name":"Victor (Japan)","ror":"https://ror.org/04b0q3m21","country_code":"JP","type":"company","lineage":["https://openalex.org/I3018882396"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tian, Chenyu","raw_affiliation_strings":["Victor"],"affiliations":[{"raw_affiliation_string":"Victor","institution_ids":["https://openalex.org/I3018882396"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086394288","display_name":"George P. Chan","orcid":null},"institutions":[{"id":"https://openalex.org/I3018882396","display_name":"Victor (Japan)","ror":"https://ror.org/04b0q3m21","country_code":"JP","type":"company","lineage":["https://openalex.org/I3018882396"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Chan, George P.","raw_affiliation_strings":["Victor"],"affiliations":[{"raw_affiliation_string":"Victor","institution_ids":["https://openalex.org/I3018882396"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109957352","display_name":"Wai Kin","orcid":null},"institutions":[{"id":"https://openalex.org/I3018882396","display_name":"Victor (Japan)","ror":"https://ror.org/04b0q3m21","country_code":"JP","type":"company","lineage":["https://openalex.org/I3018882396"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kin, Wai","raw_affiliation_strings":["Victor"],"affiliations":[{"raw_affiliation_string":"Victor","institution_ids":["https://openalex.org/I3018882396"]}]},{"author_position":"last","author":{"id":null,"display_name":"Chan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chan","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100392397"],"corresponding_institution_ids":["https://openalex.org/I3018882396"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9929999709129333,"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/T11106","display_name":"Data Management and Algorithms","score":0.9645000100135803,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.7566465139389038},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7520161271095276},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.698732316493988},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5891903638839722},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4636361002922058},{"id":"https://openalex.org/keywords/temporal-database","display_name":"Temporal database","score":0.44483089447021484},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4117591381072998},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3309706449508667},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3257450461387634}],"concepts":[{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.7566465139389038},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7520161271095276},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.698732316493988},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5891903638839722},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4636361002922058},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.44483089447021484},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4117591381072998},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3309706449508667},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3257450461387634},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2304.09182","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2304.09182","pdf_url":"https://arxiv.org/pdf/2304.09182","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2304.09182","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2304.09182","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2304.09182","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2304.09182","pdf_url":"https://arxiv.org/pdf/2304.09182","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2121191339","display_name":null,"funder_award_id":"50000","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2195155527","display_name":null,"funder_award_id":"WDZC20200818121348001","funder_id":"https://openalex.org/F4320326705","funder_display_name":"Science, Technology and Innovation Commission of Shenzhen Municipality"},{"id":"https://openalex.org/G2984240132","display_name":null,"funder_award_id":"48001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3757194791","display_name":null,"funder_award_id":"JCYJ20","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G384178317","display_name":null,"funder_award_id":"02008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4761585152","display_name":null,"funder_award_id":"JCYJ20210324135011030","funder_id":"https://openalex.org/F4320326705","funder_display_name":"Science, Technology and Innovation Commission of Shenzhen Municipality"},{"id":"https://openalex.org/G4785922630","display_name":null,"funder_award_id":"2020020","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5486152420","display_name":null,"funder_award_id":"202002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5881942141","display_name":null,"funder_award_id":"202103","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6298785130","display_name":null,"funder_award_id":"71971127","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6437360502","display_name":null,"funder_award_id":"2021032","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6466967754","display_name":null,"funder_award_id":"20200201","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7502554012","display_name":null,"funder_award_id":"KCXFZ202002011010487","funder_id":"https://openalex.org/F4320326705","funder_display_name":"Science, Technology and Innovation Commission of Shenzhen Municipality"},{"id":"https://openalex.org/G8161904097","display_name":null,"funder_award_id":"202008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326705","display_name":"Science, Technology and Innovation Commission of Shenzhen Municipality","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4366728284.pdf","grobid_xml":"https://content.openalex.org/works/W4366728284.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2181530120","https://openalex.org/W4211215373","https://openalex.org/W2024529227","https://openalex.org/W2055961818","https://openalex.org/W1574575415","https://openalex.org/W3144172081","https://openalex.org/W3179858851","https://openalex.org/W3028371478","https://openalex.org/W2081476516","https://openalex.org/W2581984549"],"abstract_inverted_index":{"Spatiotemporal":[0],"(ST)":[1],"data":[2,18,35,63,73],"collected":[3],"by":[4],"sensors":[5],"can":[6],"be":[7],"represented":[8],"as":[9],"multi-variate":[10],"time":[11,110],"series,":[12],"which":[13,46],"is":[14,52,57,75,93,131],"a":[15,94],"sequence":[16],"of":[17,24,30,41,82,128],"points":[19],"listed":[20],"in":[21,68,88,109],"an":[22],"order":[23],"time.":[25],"Despite":[26],"the":[27,33,39,62,80,89,106,121,125,129],"vast":[28],"amount":[29],"useful":[31],"information,":[32],"ST":[34],"usually":[36],"suffer":[37],"from":[38],"issue":[40],"missing":[42],"or":[43,112],"incomplete":[44],"data,":[45],"also":[47],"limits":[48],"its":[49],"applications.":[50,66,100],"Imputation":[51],"one":[53],"viable":[54],"solution":[55],"and":[56,92,124],"often":[58],"used":[59],"to":[60,79,118],"prepossess":[61],"for":[64,98],"further":[65,99],"However,":[67],"practice,":[69,71],"n":[70],"spatiotemporal":[72,83,122],"imputation":[74],"quite":[76],"difficult":[77],"due":[78],"complexity":[81],"dependencies":[84,108],"with":[85],"dynamic":[86],"changes":[87],"traffic":[90],"network":[91],"crucial":[95],"prepossessing":[96],"task":[97],"Existing":[101],"approaches":[102],"mostly":[103],"only":[104],"capture":[105],"temporal":[107],"series":[111],"static":[113],"spatial":[114],"dependencies.":[115],"They":[116],"fail":[117],"directly":[119],"model":[120],"dependencies,":[123],"representation":[126],"ability":[127],"models":[130],"relatively":[132],"limited.":[133]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}