{"id":"https://openalex.org/W4320507233","doi":"https://doi.org/10.1145/3579051.3579058","title":"An Urban Traffic Knowledge Graph-Driven Spatial-Temporal Graph Convolutional Network for Traffic Flow Prediction","display_name":"An Urban Traffic Knowledge Graph-Driven Spatial-Temporal Graph Convolutional Network for Traffic Flow Prediction","publication_year":2022,"publication_date":"2022-10-27","ids":{"openalex":"https://openalex.org/W4320507233","doi":"https://doi.org/10.1145/3579051.3579058"},"language":"en","primary_location":{"id":"doi:10.1145/3579051.3579058","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3579051.3579058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th International Joint Conference on Knowledge Graphs","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/A5035847297","display_name":"Chengbiao Yang","orcid":"https://orcid.org/0000-0001-7393-6174"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chengbiao Yang","raw_affiliation_strings":["School of Computer Science and Engineering, Southeast University, China"],"raw_orcid":"https://orcid.org/0000-0001-7393-6174","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Southeast University, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034606659","display_name":"Guilin Qi","orcid":"https://orcid.org/0000-0003-0150-7236"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guilin Qi","raw_affiliation_strings":["School of Computer Science and Engineering, Southeast University, China"],"raw_orcid":"https://orcid.org/0000-0003-0150-7236","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Southeast University, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5035847297"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":1.1877,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.76316348,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"110","last_page":"114"},"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":0.9955999851226807,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9905999898910522,"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":0.7313491106033325},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6175254583358765},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.5492753982543945},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.5310447812080383},{"id":"https://openalex.org/keywords/floating-car-data","display_name":"Floating car data","score":0.4495280981063843},{"id":"https://openalex.org/keywords/traffic-congestion-reconstruction-with-kerners-three-phase-theory","display_name":"Traffic congestion reconstruction with Kerner's three-phase theory","score":0.4452466070652008},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.43289855122566223},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40168875455856323},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.30509287118911743},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.25959354639053345},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.23037537932395935},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11344775557518005}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7313491106033325},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6175254583358765},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.5492753982543945},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.5310447812080383},{"id":"https://openalex.org/C64093975","wikidata":"https://www.wikidata.org/wiki/Q356677","display_name":"Floating car data","level":3,"score":0.4495280981063843},{"id":"https://openalex.org/C25492975","wikidata":"https://www.wikidata.org/wiki/Q960570","display_name":"Traffic congestion reconstruction with Kerner's three-phase theory","level":3,"score":0.4452466070652008},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.43289855122566223},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40168875455856323},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.30509287118911743},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.25959354639053345},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.23037537932395935},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11344775557518005}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3579051.3579058","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3579051.3579058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th International Joint Conference on Knowledge Graphs","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1984969638","https://openalex.org/W2004353783","https://openalex.org/W2047074934","https://openalex.org/W2108196201","https://openalex.org/W2250342289","https://openalex.org/W2533328922","https://openalex.org/W2572939427","https://openalex.org/W2613331518","https://openalex.org/W2756203131","https://openalex.org/W2808871417","https://openalex.org/W2901504064","https://openalex.org/W2944500953","https://openalex.org/W3103720336","https://openalex.org/W3109074851","https://openalex.org/W6607666538"],"related_works":["https://openalex.org/W4390987329","https://openalex.org/W2972320057","https://openalex.org/W4220875044","https://openalex.org/W2587362999","https://openalex.org/W4386289889","https://openalex.org/W2074943018","https://openalex.org/W2009112536","https://openalex.org/W1977405947","https://openalex.org/W1977153226","https://openalex.org/W4361199786"],"abstract_inverted_index":{"Traffic":[0],"flow":[1,94,113,146,156],"prediction":[2],"is":[3,66,80],"a":[4,161],"critical":[5],"issue":[6],"for":[7,92,111],"researchers":[8],"and":[9,21,47,131,154],"practitioners":[10],"in":[11,33],"the":[12,18,41,48,51,57,61,67,84,88,126,137,144,151,158,174],"field":[13],"of":[14,23,43,50,60,63,69,87,160,176],"transportation.":[15],"Due":[16],"to":[17,82,142],"high":[19],"nonlinearity":[20],"complexity":[22],"traffic":[24,64,90,93,104,112,120,139,145,155,171],"data,":[25],"deep":[26],"learning":[27],"approaches":[28],"have":[29],"attracted":[30],"much":[31],"interest":[32],"recent":[34],"years.":[35],"However,":[36],"existing":[37],"studies":[38],"seldom":[39],"consider":[40],"topology":[42,86],"these":[44,70],"urban":[45,89,103,119,138],"roads":[46,130],"connectivity":[49,68,128],"monitor":[52,132],"sensors.":[53,133],"As":[54],"we":[55,100,135,149],"know,":[56],"real":[58],"cause":[59],"spread":[62],"congestion":[65],"road":[71],"segments,":[72],"rather":[73],"than":[74],"their":[75],"spatial":[76],"proximity.":[77],"But":[78],"it":[79],"challenging":[81],"model":[83],"dynamic":[85],"networks":[91,110],"prediction.":[95,114],"In":[96],"this":[97],"vision":[98],"paper,":[99],"present":[101],"an":[102,118],"knowledge":[105,121,140,152],"graph-driven":[106],"spatial-temporal":[107,162],"graph":[108,122,141,153,163],"convolutional":[109,164],"We":[115],"first":[116],"construct":[117],"that":[123],"can":[124],"represent":[125],"physical":[127],"between":[129],"Then,":[134],"use":[136],"improve":[143],"networks.":[147,166],"Finally,":[148],"combine":[150],"as":[157],"input":[159],"backbone":[165],"Experiments":[167],"on":[168],"two":[169],"real-world":[170],"datasets":[172],"verify":[173],"effectiveness":[175],"our":[177],"approach.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}