{"id":"https://openalex.org/W4281763058","doi":"https://doi.org/10.1109/tkde.2022.3179646","title":"A Graph and Attentive Multi-Path Convolutional Network for Traffic Prediction","display_name":"A Graph and Attentive Multi-Path Convolutional Network for Traffic Prediction","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4281763058","doi":"https://doi.org/10.1109/tkde.2022.3179646"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2022.3179646","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3179646","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-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/A5022290876","display_name":"Jianzhong Qi","orcid":"https://orcid.org/0000-0001-6501-9050"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Jianzhong Qi","raw_affiliation_strings":["School of Computing and Information Systems, The University of Melbourne, Victoria 3010 Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing and Information Systems, The University of Melbourne, Victoria 3010 Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042518350","display_name":"Zhuowei Zhao","orcid":"https://orcid.org/0000-0002-6891-6432"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zhuowei Zhao","raw_affiliation_strings":["School of Computing and Information Systems, The University of Melbourne, Victoria 3010 Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing and Information Systems, The University of Melbourne, Victoria 3010 Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035347745","display_name":"Egemen Tanin","orcid":"https://orcid.org/0000-0001-5014-1969"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Egemen Tanin","raw_affiliation_strings":["School of Computing and Information Systems, The University of Melbourne, Victoria 3010 Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing and Information Systems, The University of Melbourne, Victoria 3010 Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033201088","display_name":"Tingru Cui","orcid":"https://orcid.org/0000-0002-7899-1372"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Tingru Cui","raw_affiliation_strings":["School of Computing and Information Systems, The University of Melbourne, Victoria 3010 Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing and Information Systems, The University of Melbourne, Victoria 3010 Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023470461","display_name":"Neema Nassir","orcid":"https://orcid.org/0000-0001-7804-7851"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Neema Nassir","raw_affiliation_strings":["Department of Infrastructure Engineering, The University of Melbourne, Victoria 3010 Australia"],"affiliations":[{"raw_affiliation_string":"Department of Infrastructure Engineering, The University of Melbourne, Victoria 3010 Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021264543","display_name":"Majid Sarvi","orcid":"https://orcid.org/0000-0001-7585-5837"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Majid Sarvi","raw_affiliation_strings":["Department of Infrastructure Engineering, The University of Melbourne, Victoria 3010 Australia"],"affiliations":[{"raw_affiliation_string":"Department of Infrastructure Engineering, The University of Melbourne, Victoria 3010 Australia","institution_ids":["https://openalex.org/I165779595"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5022290876"],"corresponding_institution_ids":["https://openalex.org/I165779595"],"apc_list":null,"apc_paid":null,"fwci":3.9162,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.94101192,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"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":0.995199978351593,"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":0.9901000261306763,"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":0.7885043621063232},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6077861785888672},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5576512217521667},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48211121559143066},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4540983736515045},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.4293912947177887},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.42102378606796265},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37816929817199707},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2828230857849121},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.14705577492713928},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.12002107501029968}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7885043621063232},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6077861785888672},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5576512217521667},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48211121559143066},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4540983736515045},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.4293912947177887},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.42102378606796265},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37816929817199707},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2828230857849121},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.14705577492713928},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.12002107501029968}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2022.3179646","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3179646","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6499999761581421}],"awards":[{"id":"https://openalex.org/G3738055978","display_name":null,"funder_award_id":"FEIT Platform Interdisciplinary Grant (2020)","funder_id":"https://openalex.org/F4320320974","funder_display_name":"University of Melbourne"}],"funders":[{"id":"https://openalex.org/F4320320974","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1973943669","https://openalex.org/W2113298739","https://openalex.org/W2156206597","https://openalex.org/W2519091744","https://openalex.org/W2528639018","https://openalex.org/W2530386080","https://openalex.org/W2560675361","https://openalex.org/W2579495707","https://openalex.org/W2756203131","https://openalex.org/W2788284887","https://openalex.org/W2792402990","https://openalex.org/W2807894308","https://openalex.org/W2809593532","https://openalex.org/W2897951893","https://openalex.org/W2900874631","https://openalex.org/W2903871660","https://openalex.org/W2904349291","https://openalex.org/W2904832339","https://openalex.org/W2905082218","https://openalex.org/W2922509574","https://openalex.org/W2949732208","https://openalex.org/W2950817888","https://openalex.org/W2951653466","https://openalex.org/W2962687116","https://openalex.org/W2962756421","https://openalex.org/W2963241486","https://openalex.org/W2963358464","https://openalex.org/W2965341826","https://openalex.org/W2969294606","https://openalex.org/W2970929262","https://openalex.org/W2972229264","https://openalex.org/W2994901268","https://openalex.org/W2996847713","https://openalex.org/W2997848713","https://openalex.org/W3003426638","https://openalex.org/W3004988234","https://openalex.org/W3015712039","https://openalex.org/W3038981236","https://openalex.org/W3055194044","https://openalex.org/W3103720336","https://openalex.org/W3159953606","https://openalex.org/W3174022889","https://openalex.org/W3174672503","https://openalex.org/W4288094782","https://openalex.org/W4385245566","https://openalex.org/W6730235577","https://openalex.org/W6739901393","https://openalex.org/W6746015598","https://openalex.org/W6749578362","https://openalex.org/W6757917161","https://openalex.org/W6761121490","https://openalex.org/W6767402564","https://openalex.org/W6767610075","https://openalex.org/W6773968902","https://openalex.org/W6780221082"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W4293226380","https://openalex.org/W2183306018","https://openalex.org/W2549990292","https://openalex.org/W2345479200","https://openalex.org/W2951819827","https://openalex.org/W2849310602","https://openalex.org/W4313906399","https://openalex.org/W4321487865","https://openalex.org/W3103753037"],"abstract_inverted_index":{"Traffic":[0],"prediction":[1,149,180,189,196],"is":[2,137],"an":[3,141,145],"important":[4],"and":[5,14,29,58,167,191],"yet":[6],"highly":[7],"challenging":[8],"problem":[9],"due":[10],"to":[11,36,82,100,116,184],"the":[12,23,50,56,67,75,105,118,129,148,153],"complexity":[13],"constantly":[15],"changing":[16],"nature":[17],"of":[18,74,121,124,147,156,188,195],"traffic":[19,38,42,63,96,126,131,157,168,179],"systems.":[20],"To":[21,65,103],"address":[22],"challenges,":[24],"we":[25,70,108],"propose":[26,71],"a":[27,45,72,89,110,134],"graph":[28,76,86],"attentive":[30],"multi-path":[31,111],"convolutional":[32,77,112],"network":[33,48,78,85,114],"(GAMCN)":[34],"model":[35,53,66,104,162,176],"predict":[37],"conditions":[39,97,127],"such":[40],"as":[41],"speed":[43],"across":[44],"given":[46],"road":[47,84,165],"into":[49,88],"future.":[51],"Our":[52],"focuses":[54],"on":[55,128,163],"spatial":[57,68],"temporal":[59,106],"factors":[60],"that":[61,174],"impact":[62,120,136],"conditions.":[64,132,158],"factors,":[69,107],"variant":[73],"(GCN)":[79],"named":[80],"LPGCN":[81],"embed":[83],"vertices":[87,93],"latent":[90],"space,":[91],"where":[92],"with":[94],"correlated":[95],"are":[98],"close":[99],"each":[101],"other.":[102],"use":[109],"neural":[113],"(CNN)":[115],"learn":[117],"joint":[119,135],"different":[122],"combinations":[123],"past":[125],"future":[130],"Such":[133],"further":[138],"modulated":[139],"by":[140,182],"attention":[142],"generated":[143],"from":[144],"embedding":[146],"time,":[150],"which":[151],"encodes":[152],"periodic":[154],"patterns":[155],"We":[159],"evaluate":[160],"our":[161,175],"real-world":[164],"networks":[166],"data.":[169],"The":[170],"experimental":[171],"results":[172],"show":[173],"outperforms":[177],"state-of-art":[178],"models":[181],"up":[183],"18.9%":[185],"in":[186,193],"terms":[187,194],"errors":[190],"23.4%":[192],"efficiency.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":11}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}