{"id":"https://openalex.org/W4306317916","doi":"https://doi.org/10.1145/3511808.3557705","title":"ST-GAT","display_name":"ST-GAT","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306317916","doi":"https://doi.org/10.1145/3511808.3557705"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557705","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557705","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","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/A5083076695","display_name":"Junho Song","orcid":"https://orcid.org/0000-0003-3592-7669"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junho Song","raw_affiliation_strings":["Hanyang University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hanyang University, Seoul, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073211146","display_name":"Ji\u2010Won Son","orcid":"https://orcid.org/0000-0002-4266-0889"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jiwon Son","raw_affiliation_strings":["Hanyang University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hanyang University, Seoul, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028076210","display_name":"Dong-hyuk Seo","orcid":"https://orcid.org/0000-0002-6338-1336"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dong-hyuk Seo","raw_affiliation_strings":["Hanyang University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hanyang University, Seoul, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066977998","display_name":"Kyungsik Han","orcid":"https://orcid.org/0000-0001-5535-0081"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyungsik Han","raw_affiliation_strings":["Hanyang University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hanyang University, Seoul, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013014129","display_name":"Namhyuk Kim","orcid":"https://orcid.org/0000-0003-3567-8260"},"institutions":[{"id":"https://openalex.org/I49946491","display_name":"Hyundai Motors (South Korea)","ror":"https://ror.org/016kvft77","country_code":"KR","type":"company","lineage":["https://openalex.org/I197312522","https://openalex.org/I49946491"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Namhyuk Kim","raw_affiliation_strings":["Hyundai Motor Company, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hyundai Motor Company, Seoul, South Korea","institution_ids":["https://openalex.org/I49946491"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100656150","display_name":"Sang\u2010Wook Kim","orcid":"https://orcid.org/0000-0002-6345-9084"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sang-Wook Kim","raw_affiliation_strings":["Hanyang University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hanyang University, Seoul, South Korea","institution_ids":["https://openalex.org/I4575257"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4500","last_page":"4504"},"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9962000250816345,"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"}},{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9951000213623047,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7190194129943848},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6265466809272766},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6086742281913757},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5721602439880371},{"id":"https://openalex.org/keywords/traffic-speed","display_name":"Traffic speed","score":0.5472001433372498},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4527093768119812},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4114193618297577},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3852199614048004},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3730287551879883},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32638782262802124},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3188307285308838}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7190194129943848},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6265466809272766},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6086742281913757},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5721602439880371},{"id":"https://openalex.org/C2993660032","wikidata":"https://www.wikidata.org/wiki/Q746984","display_name":"Traffic speed","level":2,"score":0.5472001433372498},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4527093768119812},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4114193618297577},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3852199614048004},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3730287551879883},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32638782262802124},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3188307285308838},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3511808.3557705","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557705","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2004353783","https://openalex.org/W2528639018","https://openalex.org/W2530386080","https://openalex.org/W2756203131","https://openalex.org/W2775717462","https://openalex.org/W2901504064","https://openalex.org/W2945991855","https://openalex.org/W2950817888","https://openalex.org/W2962790412","https://openalex.org/W2965341826","https://openalex.org/W2965399951","https://openalex.org/W2996847713","https://openalex.org/W2997848713","https://openalex.org/W2998559444","https://openalex.org/W3010546705","https://openalex.org/W3011204221","https://openalex.org/W3012562343","https://openalex.org/W3035580605","https://openalex.org/W3080253043","https://openalex.org/W3080422828","https://openalex.org/W3094588037","https://openalex.org/W3103720336","https://openalex.org/W3147177457","https://openalex.org/W3171958173","https://openalex.org/W3175154343","https://openalex.org/W3175786688","https://openalex.org/W4206914189","https://openalex.org/W4289533915"],"related_works":["https://openalex.org/W1496222301","https://openalex.org/W3207760230","https://openalex.org/W1590307681","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703","https://openalex.org/W41015297","https://openalex.org/W4280645561"],"abstract_inverted_index":{"Spatio-temporal":[0],"models,":[1],"which":[2],"combine":[3],"GNNs":[4],"(Graph":[5],"Neural":[6,11],"Networks)":[7],"and":[8,29,40,53,82,106,126,167],"RNNs":[9],"(Recurrent":[10],"Networks),":[12],"have":[13],"shown":[14],"state-of-the-art":[15,159],"accuracy":[16],"in":[17,35,51,80,147,164,175],"traffic":[18,86,120,149,177],"speed":[19,87,150],"prediction.":[20,88],"However,":[21],"we":[22,64,90],"find":[23],"that":[24,97],"they":[25],"consider":[26],"the":[27,36,47,59,67,99,118,124,127,142,145,153,169],"spatial":[28],"temporal":[30],"dependencies":[31,72,102],"between":[32,73],"speeds":[33,50,75,121],"separately":[34],"two":[37,74],"(i.e.,":[38,161],"space":[39,52,81],"time)":[41],"dimensions,":[42],"thereby":[43],"unable":[44],"to":[45,116],"exploit":[46],"joint-dependencies":[48],"of":[49,69,144,155,171],"time.":[54],"In":[55],"this":[56],"paper,":[57],"with":[58,136],"evidence":[60],"via":[61],"preliminary":[62],"analysis,":[63],"point":[65],"out":[66],"importance":[68],"considering":[70],"individual":[71],"from":[76,132],"all":[77],"possible":[78],"points":[79],"time":[83],"for":[84],"accurate":[85],"Then,":[89],"propose":[91],"an":[92],"Individual":[93,100],"Spatio-Temporal":[94,101,108],"graph":[95],"(IST-graph)":[96],"represents":[98],"(IST-dependencies)":[103],"very":[104],"effectively":[105],"a":[107,113],"Graph":[109],"ATtention":[110],"network":[111],"(ST-GAT),":[112],"novel":[114],"model":[115],"predict":[117],"future":[119],"based":[122],"on":[123],"IST-graph":[125,146],"attention":[128],"mechanism.":[129],"The":[130],"results":[131],"our":[133,172],"extensive":[134],"evaluation":[135],"five":[137],"real-world":[138],"datasets":[139],"demonstrate":[140],"(1)":[141],"effectiveness":[143],"modeling":[148],"data,":[151],"(2)":[152],"superiority":[154],"ST-GAT":[156,173],"over":[157],"5":[158],"models":[160],"2-33%":[162],"gains)":[163],"prediction":[165],"accuracy,":[166],"(3)":[168],"robustness":[170],"even":[174],"abnormal":[176],"situations.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2022-10-16T00:00:00"}
