{"id":"https://openalex.org/W4366306854","doi":"https://doi.org/10.1109/icite56321.2022.10101407","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":2022,"publication_date":"2022-11-11","ids":{"openalex":"https://openalex.org/W4366306854","doi":"https://doi.org/10.1109/icite56321.2022.10101407"},"language":"en","primary_location":{"id":"doi:10.1109/icite56321.2022.10101407","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icite56321.2022.10101407","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 7th International Conference on Intelligent Transportation Engineering (ICITE)","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/A5044960023","display_name":"Jiang Li","orcid":"https://orcid.org/0000-0002-9856-8002"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Li Jiang","raw_affiliation_strings":["Tsinghua University,Tsinghua-Berkeley Shenzhen Institute,Shenzhen,China","Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Tsinghua-Berkeley Shenzhen Institute,Shenzhen,China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111755875","display_name":"Ting Zhang","orcid":"https://orcid.org/0009-0003-0124-6758"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Zhang","raw_affiliation_strings":["Tsinghua University,Tsinghua-Berkeley Shenzhen Institute,Shenzhen,China","Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Tsinghua-Berkeley Shenzhen Institute,Shenzhen,China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]},{"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/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiruyi Zuo","raw_affiliation_strings":["Tsinghua University,Tsinghua-Berkeley Shenzhen Institute,Shenzhen,China","Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Tsinghua-Berkeley Shenzhen Institute,Shenzhen,China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022520101","display_name":"Chenyu Tian","orcid":"https://orcid.org/0000-0002-7748-5873"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenyu Tian","raw_affiliation_strings":["Tsinghua University,Alibaba Group,Hangzhou,China","Alibaba Group, Tsinghua University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Alibaba Group,Hangzhou,China","institution_ids":["https://openalex.org/I45928872","https://openalex.org/I99065089"]},{"raw_affiliation_string":"Alibaba Group, Tsinghua University, Hangzhou, China","institution_ids":["https://openalex.org/I45928872","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086394288","display_name":"George P. Chan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"George P. Chan","raw_affiliation_strings":["Loudonville Christian School,Loudonville,NY","Loudonville Christian School, Loudonville, NY"],"affiliations":[{"raw_affiliation_string":"Loudonville Christian School,Loudonville,NY","institution_ids":[]},{"raw_affiliation_string":"Loudonville Christian School, Loudonville, NY","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108743840","display_name":"Wai Kin Victor Chan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wai Kin Victor Chan","raw_affiliation_strings":["Tsinghua University,Tsinghua-Berkeley Shenzhen Institute,Shenzhen,China","Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Tsinghua-Berkeley Shenzhen Institute,Shenzhen,China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5044960023"],"corresponding_institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.2117,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51640324,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"14","last_page":"19"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9976000189781189,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8028254508972168},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6875503063201904},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.6434445977210999},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.559739887714386},{"id":"https://openalex.org/keywords/temporal-database","display_name":"Temporal database","score":0.5412982702255249},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4385189116001129},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4194610118865967},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4184167981147766},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3401567339897156},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32778745889663696},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.0872129499912262}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8028254508972168},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6875503063201904},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.6434445977210999},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.559739887714386},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.5412982702255249},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4385189116001129},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4194610118865967},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4184167981147766},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3401567339897156},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32778745889663696},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0872129499912262},{"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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":1,"locations":[{"id":"doi:10.1109/icite56321.2022.10101407","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icite56321.2022.10101407","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 7th International Conference on Intelligent Transportation Engineering (ICITE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2008925288","https://openalex.org/W2059971613","https://openalex.org/W2120718561","https://openalex.org/W2163150789","https://openalex.org/W2334686861","https://openalex.org/W2423557781","https://openalex.org/W2519091744","https://openalex.org/W2762772695","https://openalex.org/W2899300491","https://openalex.org/W2963214893","https://openalex.org/W2980537499","https://openalex.org/W3004584189","https://openalex.org/W3088611441","https://openalex.org/W3135694489","https://openalex.org/W3210056525","https://openalex.org/W3215493153","https://openalex.org/W4244133811","https://openalex.org/W4297790320","https://openalex.org/W6725627145","https://openalex.org/W6761580696","https://openalex.org/W6780226713"],"related_works":["https://openalex.org/W2181530120","https://openalex.org/W4211215373","https://openalex.org/W2024529227","https://openalex.org/W1574575415","https://openalex.org/W3144172081","https://openalex.org/W3179858851","https://openalex.org/W3028371478","https://openalex.org/W2081476516","https://openalex.org/W2581984549","https://openalex.org/W3123177881"],"abstract_inverted_index":{"Spatiotemporal":[0],"(ST)":[1],"data":[2,18,35,62,72,148,205],"collected":[3],"by":[4,199],"sensors":[5],"can":[6],"be":[7],"represented":[8],"as":[9],"multi-variate":[10],"time":[11,109],"series,":[12],"which":[13,46],"is":[14,52,74,92,130],"a":[15,93,145,171],"sequence":[16],"of":[17,24,30,41,81,127,181,195],"points":[19],"listed":[20],"in":[21,67,87,108,203],"an":[22],"order":[23],"time.":[25],"Despite":[26],"the":[27,33,39,61,79,88,105,120,124,128,136,178,193],"vast":[28],"amount":[29],"useful":[31],"information,":[32],"ST":[34,147],"usually":[36],"suffers":[37],"from":[38],"issue":[40],"missing":[42],"or":[43,111],"incomplete":[44],"data,":[45,142],"also":[47],"limits":[48],"its":[49],"applications.":[50,65,99],"Imputation":[51],"one":[53],"viable":[54],"solution":[55],"and":[56,91,123,140,153,162],"often":[57],"used":[58],"to":[59,78,117,158,176],"prepossess":[60],"for":[63,97],"further":[64,98],"However,":[66],"practice,":[68,70],"n":[69],"spatiotemporal":[71,82,121],"imputation":[73,149],"quite":[75],"difficult":[76],"due":[77],"complexity":[80],"dependencies":[83,107,139,161],"with":[84],"dynamic":[85,163],"changes":[86],"traffic":[89],"network":[90],"crucial":[94],"prepossessing":[95],"task":[96],"Existing":[100],"approaches":[101],"mostly":[102],"only":[103],"capture":[104,135,159],"temporal":[106],"series":[110],"static":[112],"spatial":[113,164],"dependencies.":[114],"They":[115],"fail":[116],"directly":[118],"model":[119,169],"dependencies,":[122,165],"representation":[125],"ability":[126],"models":[129],"relatively":[131],"limited.":[132],"To":[133],"better":[134],"complex":[137],"spatial-temporal":[138],"impute":[141],"we":[143],"propose":[144],"new":[146],"model.":[150],"Temporal":[151],"convolution":[152],"self-attention":[154],"networks":[155],"are":[156],"utilized":[157],"long-term":[160],"respectively.":[166],"Furthermore,":[167],"our":[168,196],"develops":[170],"novel":[172],"self-learning":[173],"node":[174],"embeddings":[175],"learn":[177],"intrinsic":[179],"attributes":[180],"different":[182],"sensors.":[183],"An":[184],"end-to-end":[185],"framework":[186,198],"incorporates":[187],"these":[188],"elements.":[189],"We":[190],"empirically":[191],"illustrate":[192],"benefit":[194],"proposed":[197],"comparing":[200],"other":[201],"algorithms":[202],"real-world":[204],"sets.":[206]},"counts_by_year":[{"year":2025,"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"}
