{"id":"https://openalex.org/W2965399951","doi":"https://doi.org/10.24963/ijcai.2019/317","title":"GSTNet: Global Spatial-Temporal Network for Traffic Flow Prediction","display_name":"GSTNet: Global Spatial-Temporal Network for Traffic Flow Prediction","publication_year":2019,"publication_date":"2019-07-28","ids":{"openalex":"https://openalex.org/W2965399951","doi":"https://doi.org/10.24963/ijcai.2019/317","mag":"2965399951"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2019/317","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/317","pdf_url":"https://www.ijcai.org/proceedings/2019/0317.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2019/0317.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102777524","display_name":"Shen Fang","orcid":"https://orcid.org/0000-0002-2154-6737"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shen Fang","raw_affiliation_strings":["NLPR, Institute of Automation, Chinese Academy of Sciences","School of Artificial Intelligence, University of Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"NLPR, Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100348836","display_name":"Qi Zhang","orcid":"https://orcid.org/0009-0000-4167-8369"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Zhang","raw_affiliation_strings":["NLPR, Institute of Automation, Chinese Academy of Sciences","School of Artificial Intelligence, University of Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"NLPR, Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100675867","display_name":"Gaofeng Meng","orcid":"https://orcid.org/0000-0002-7103-6321"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gaofeng Meng","raw_affiliation_strings":["NLPR, Institute of Automation, Chinese Academy of Sciences","School of Artificial Intelligence, University of Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"NLPR, Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040673285","display_name":"Shiming Xiang","orcid":"https://orcid.org/0000-0002-2089-9733"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiming Xiang","raw_affiliation_strings":["NLPR, Institute of Automation, Chinese Academy of Sciences","School of Artificial Intelligence, University of Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"NLPR, Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100435212","display_name":"Chunhong Pan","orcid":"https://orcid.org/0000-0001-7433-4474"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunhong Pan","raw_affiliation_strings":["NLPR, Institute of Automation, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"NLPR, Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102777524"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":14.1021,"has_fulltext":false,"cited_by_count":174,"citation_normalized_percentile":{"value":0.99327994,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2286","last_page":"2293"},"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":0.989300012588501,"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":0.9800000190734863,"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":0.7301981449127197},{"id":"https://openalex.org/keywords/temporal-resolution","display_name":"Temporal resolution","score":0.5656420588493347},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5138176083564758},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48215290904045105},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.46523991227149963},{"id":"https://openalex.org/keywords/spatial-network","display_name":"Spatial network","score":0.4513964056968689},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.4424828588962555},{"id":"https://openalex.org/keywords/flow-network","display_name":"Flow network","score":0.41921672224998474},{"id":"https://openalex.org/keywords/spatial-correlation","display_name":"Spatial correlation","score":0.4181120991706848},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.41010621190071106},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1331568956375122},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.10126075148582458},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.09673762321472168},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0956428050994873}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7301981449127197},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.5656420588493347},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5138176083564758},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48215290904045105},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.46523991227149963},{"id":"https://openalex.org/C53471067","wikidata":"https://www.wikidata.org/wiki/Q7574076","display_name":"Spatial network","level":2,"score":0.4513964056968689},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.4424828588962555},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.41921672224998474},{"id":"https://openalex.org/C150060386","wikidata":"https://www.wikidata.org/wiki/Q7574054","display_name":"Spatial correlation","level":2,"score":0.4181120991706848},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.41010621190071106},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1331568956375122},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.10126075148582458},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.09673762321472168},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0956428050994873},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2019/317","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/317","pdf_url":"https://www.ijcai.org/proceedings/2019/0317.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2019/317","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/317","pdf_url":"https://www.ijcai.org/proceedings/2019/0317.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6600000262260437}],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2282123724","display_name":null,"funder_award_id":"91646207","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3069996871","display_name":null,"funder_award_id":"61773377","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G348298515","display_name":null,"funder_award_id":"6177337","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7033253288","display_name":null,"funder_award_id":"Grants","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"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2965399951.pdf","grobid_xml":"https://content.openalex.org/works/W2965399951.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W637153065","https://openalex.org/W1522301498","https://openalex.org/W1662382123","https://openalex.org/W1924770834","https://openalex.org/W2012051283","https://openalex.org/W2021153764","https://openalex.org/W2036785686","https://openalex.org/W2194775991","https://openalex.org/W2465015709","https://openalex.org/W2519091744","https://openalex.org/W2528639018","https://openalex.org/W2558460151","https://openalex.org/W2560675361","https://openalex.org/W2611552022","https://openalex.org/W2624190409","https://openalex.org/W2782920454","https://openalex.org/W2788134583","https://openalex.org/W2791999218","https://openalex.org/W2807894308","https://openalex.org/W2811135961","https://openalex.org/W2884738862","https://openalex.org/W2890671550","https://openalex.org/W2963076818","https://openalex.org/W2963358464","https://openalex.org/W2964015378","https://openalex.org/W2964321699","https://openalex.org/W3103720336","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W1988032185","https://openalex.org/W4282841357","https://openalex.org/W2101008856","https://openalex.org/W2144229794","https://openalex.org/W2142603669","https://openalex.org/W2060768920","https://openalex.org/W2531744636","https://openalex.org/W2626964394","https://openalex.org/W2964463571","https://openalex.org/W2162495504"],"abstract_inverted_index":{"Predicting":[0],"traffic":[1,4,26],"flow":[2,27],"on":[3,22,106,120],"networks":[5],"is":[6],"a":[7,63,79,84],"very":[8],"challenging":[9],"task,":[10],"due":[11],"to":[12],"the":[13,23,43,56,95,100,107,112,117,122,127],"complicated":[14],"and":[15,37,52,83,99,114,126],"dynamic":[16,58,96],"spatial-temporal":[17,59,74],"dependencies":[18,98],"between":[19],"different":[20,47],"nodes":[21,48],"network.":[24,129],"The":[25],"renders":[28],"two":[29],"types":[30],"of":[31,70,73,116],"temporal":[32,81,97],"dependencies,":[33],"including":[34],"short-term":[35],"neighboring":[36],"long-term":[38],"periodic":[39],"dependencies.":[40],"What's":[41],"more,":[42],"spatial":[44,87,102],"correlations":[45],"over":[46],"are":[49],"both":[50,121],"local":[51],"non-local.":[53],"To":[54],"capture":[55],"global":[57,85,101],"correlations,":[60],"we":[61],"propose":[62],"Global":[64],"Spatial-Temporal":[65],"Network":[66],"(GSTNet),":[67],"which":[68,91],"consists":[69],"several":[71],"layers":[72],"blocks.":[75],"Each":[76],"block":[77],"contains":[78],"multi-resolution":[80],"module":[82,88],"correlated":[86],"in":[89],"sequence,":[90],"can":[92],"simultaneously":[93],"extract":[94],"correlations.":[103],"Extensive":[104],"experiments":[105],"real":[108],"world":[109],"datasets":[110],"verify":[111],"effectiveness":[113],"superiority":[115],"proposed":[118],"method":[119],"public":[123],"transportation":[124],"network":[125],"road":[128]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":21},{"year":2024,"cited_by_count":37},{"year":2023,"cited_by_count":28},{"year":2022,"cited_by_count":35},{"year":2021,"cited_by_count":34},{"year":2020,"cited_by_count":17},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}