{"id":"https://openalex.org/W4389098736","doi":"https://doi.org/10.1145/3634913","title":"Adaptive Joint Spatio-Temporal Graph Learning Network for Traffic Data Forecasting","display_name":"Adaptive Joint Spatio-Temporal Graph Learning Network for Traffic Data Forecasting","publication_year":2023,"publication_date":"2023-11-28","ids":{"openalex":"https://openalex.org/W4389098736","doi":"https://doi.org/10.1145/3634913"},"language":"en","primary_location":{"id":"doi:10.1145/3634913","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3634913","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3634913","source":{"id":"https://openalex.org/S2503711797","display_name":"ACM Transactions on Spatial Algorithms and Systems","issn_l":"2374-0353","issn":["2374-0353","2374-0361"],"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 Spatial Algorithms and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3634913","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Tianyi Wang","orcid":"https://orcid.org/0000-0001-5120-6568"},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianyi Wang","raw_affiliation_strings":["University of Missouri Kansas City, Kansas City, USA","University of Missouri-Kansas City Division of Computing, Analytics and Mathematics, USA"],"raw_orcid":"https://orcid.org/0000-0001-5120-6568","affiliations":[{"raw_affiliation_string":"University of Missouri Kansas City, Kansas City, USA","institution_ids":["https://openalex.org/I75421653"]},{"raw_affiliation_string":"University of Missouri-Kansas City Division of Computing, Analytics and Mathematics, USA","institution_ids":["https://openalex.org/I75421653"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049219173","display_name":"Shu\u2010Ching Chen","orcid":"https://orcid.org/0000-0001-9209-390X"},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shu-Ching Chen","raw_affiliation_strings":["University of Missouri Kansas City, Kansas City, USA","University of Missouri-Kansas City Data Science and Analytics Innovation Center (dSAIC), Division of Computing, Analytics and Mathematics, USA"],"raw_orcid":"https://orcid.org/0000-0001-9209-390X","affiliations":[{"raw_affiliation_string":"University of Missouri Kansas City, Kansas City, USA","institution_ids":["https://openalex.org/I75421653"]},{"raw_affiliation_string":"University of Missouri-Kansas City Data Science and Analytics Innovation Center (dSAIC), Division of Computing, Analytics and Mathematics, USA","institution_ids":["https://openalex.org/I75421653"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I75421653"],"apc_list":null,"apc_paid":null,"fwci":0.4014,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.59914579,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"10","issue":"3","first_page":"1","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":1.0,"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":1.0,"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/T10524","display_name":"Traffic control and management","score":0.9926999807357788,"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"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9925000071525574,"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/computer-science","display_name":"Computer science","score":0.787574291229248},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5687353610992432},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.47083568572998047},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.4539602994918823},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.41775181889533997},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4101514220237732},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40059295296669006},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3750510811805725},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.28294920921325684},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.26731106638908386}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.787574291229248},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5687353610992432},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47083568572998047},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.4539602994918823},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.41775181889533997},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4101514220237732},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40059295296669006},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3750510811805725},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28294920921325684},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.26731106638908386},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3634913","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3634913","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3634913","source":{"id":"https://openalex.org/S2503711797","display_name":"ACM Transactions on Spatial Algorithms and Systems","issn_l":"2374-0353","issn":["2374-0353","2374-0361"],"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 Spatial Algorithms and Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3634913","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3634913","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3634913","source":{"id":"https://openalex.org/S2503711797","display_name":"ACM Transactions on Spatial Algorithms and Systems","issn_l":"2374-0353","issn":["2374-0353","2374-0361"],"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 Spatial Algorithms and Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.41999998688697815}],"awards":[{"id":"https://openalex.org/G3017301181","display_name":"SCC-IRG JST: Multimodal Data Analytics and Integration for Effective COVID-19, Pandemics and Compound Disaster Response and Management","funder_award_id":"2301552","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G458719144","display_name":null,"funder_award_id":"CNS-2301552","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"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4389098736.pdf","grobid_xml":"https://content.openalex.org/works/W4389098736.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W24128161","https://openalex.org/W2593463961","https://openalex.org/W2747329762","https://openalex.org/W2756203131","https://openalex.org/W2903871660","https://openalex.org/W2938555542","https://openalex.org/W2948048211","https://openalex.org/W2955819484","https://openalex.org/W2965341826","https://openalex.org/W2981927324","https://openalex.org/W2988226917","https://openalex.org/W2997848713","https://openalex.org/W3008191852","https://openalex.org/W3020001547","https://openalex.org/W3021810927","https://openalex.org/W3022353848","https://openalex.org/W3030299187","https://openalex.org/W3035466700","https://openalex.org/W3038981236","https://openalex.org/W3039628929","https://openalex.org/W3044713958","https://openalex.org/W3092530991","https://openalex.org/W3103720336","https://openalex.org/W3107194210","https://openalex.org/W3109606123","https://openalex.org/W3119139689","https://openalex.org/W3170431411","https://openalex.org/W3215457656","https://openalex.org/W3217139354","https://openalex.org/W4200002683","https://openalex.org/W4200630737","https://openalex.org/W4220776795","https://openalex.org/W4221032654","https://openalex.org/W4224211827","https://openalex.org/W4224293834","https://openalex.org/W4235154503","https://openalex.org/W4283739673","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W4390516098","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W4205302943","https://openalex.org/W2119949815","https://openalex.org/W2561132942","https://openalex.org/W2142795561","https://openalex.org/W3155418658","https://openalex.org/W2379948177","https://openalex.org/W2107949441"],"abstract_inverted_index":{"Traffic":[0],"data":[1,68],"forecasting":[2],"has":[3],"become":[4],"an":[5],"integral":[6],"part":[7],"of":[8,110],"the":[9,30,34,41,49,82,91,103,108,124,131],"intelligent":[10],"traffic":[11,23,42,50,67,87,142],"system.":[12],"Great":[13],"efforts":[14],"are":[15,45],"spent":[16],"developing":[17],"tools":[18],"and":[19,36,75,84,89,106],"techniques":[20],"to":[21,32,80,101,122],"estimate":[22],"flow":[24,143],"patterns.":[25],"Many":[26],"existing":[27],"approaches":[28],"lack":[29],"ability":[31],"model":[33,72,98,148],"complex":[35],"dynamic":[37,85],"spatio-temporal":[38,62,118],"relations":[39,134],"in":[40,47,135],"data,":[43],"which":[44],"crucial":[46],"capturing":[48,130],"dynamic.":[51],"In":[52],"this":[53],"work,":[54],"we":[55],"propose":[56],"AJSTGL,":[57],"a":[58,117],"novel":[59],"adaptive":[60,76],"joint":[61],"graph":[63,77,92,119],"learning":[64,78,93],"network":[65],"for":[66],"forecasting.":[69],"The":[70],"proposed":[71,100],"utilizes":[73],"static":[74,83],"modules":[79],"capture":[81],"spatial":[86],"patterns":[88],"optimize":[90],"process.":[94],"A":[95],"sequence-to-sequence":[96,125],"fusion":[97,126],"is":[99],"learn":[102],"temporal":[104],"correlation":[105],"combine":[107],"output":[109],"multiple":[111],"parallelized":[112],"encoders.":[113],"We":[114],"also":[115],"develop":[116],"transformer":[120],"module":[121,127],"complement":[123],"by":[128],"dynamically":[129],"time-evolving":[132],"node":[133],"long-term":[136],"intervals.":[137],"Experiments":[138],"on":[139],"three":[140],"large-scale":[141],"datasets":[144],"demonstrate":[145],"that":[146],"our":[147],"could":[149],"outperform":[150],"other":[151],"state-of-the-art":[152],"baseline":[153],"methods.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
