{"id":"https://openalex.org/W4387458773","doi":"https://doi.org/10.1142/s0218001423500295","title":"Vehicle Trajectory Completion for Automatic Number Plate Recognition Data: A Temporal Knowledge Graph-Based Method","display_name":"Vehicle Trajectory Completion for Automatic Number Plate Recognition Data: A Temporal Knowledge Graph-Based Method","publication_year":2023,"publication_date":"2023-10-01","ids":{"openalex":"https://openalex.org/W4387458773","doi":"https://doi.org/10.1142/s0218001423500295"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001423500295","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001423500295","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","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/A5053527094","display_name":"Zhe Long","orcid":"https://orcid.org/0009-0008-5960-1819"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhe Long","raw_affiliation_strings":["School of Computer Science and Engineering, Central South University, Hunan 410083, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Central South University, Hunan 410083, P. R. China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103059683","display_name":"Jinjin Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Jinjin Chen","raw_affiliation_strings":["Center for Cognitive and Brain Sciences, University of Macau, Macau SAR, P. R. China"],"affiliations":[{"raw_affiliation_string":"Center for Cognitive and Brain Sciences, University of Macau, Macau SAR, P. R. China","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064823007","display_name":"Zuping Zhang","orcid":"https://orcid.org/0000-0002-2528-7808"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zuping Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, Central South University, Hunan 410083, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Central South University, Hunan 410083, P. R. China","institution_ids":["https://openalex.org/I139660479"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5053527094"],"corresponding_institution_ids":["https://openalex.org/I139660479"],"apc_list":null,"apc_paid":null,"fwci":0.3221,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.62581501,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"37","issue":"13","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9962000250816345,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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":0.7996574640274048},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7618592977523804},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6054642200469971},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5199397802352905},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4592776894569397},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41368648409843445},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34393584728240967},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1710939109325409}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7996574640274048},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7618592977523804},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6054642200469971},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5199397802352905},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4592776894569397},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41368648409843445},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34393584728240967},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1710939109325409},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001423500295","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001423500295","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2688703275","display_name":null,"funder_award_id":"72061147004","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2109770203","https://openalex.org/W2786875762","https://openalex.org/W2798864014","https://openalex.org/W2799251491","https://openalex.org/W2890410208","https://openalex.org/W2935850529","https://openalex.org/W2981175810","https://openalex.org/W2996788697","https://openalex.org/W3006961158","https://openalex.org/W3016072985","https://openalex.org/W3018779742","https://openalex.org/W3042710080","https://openalex.org/W3117206239","https://openalex.org/W3120284467","https://openalex.org/W3128196514","https://openalex.org/W3128695267","https://openalex.org/W3147042931","https://openalex.org/W3167316272"],"related_works":["https://openalex.org/W4323768008","https://openalex.org/W1941703695","https://openalex.org/W3131574667","https://openalex.org/W4360995134","https://openalex.org/W4248382324","https://openalex.org/W3023605104","https://openalex.org/W2039473718","https://openalex.org/W2387529410","https://openalex.org/W2383578611","https://openalex.org/W2987583674"],"abstract_inverted_index":{"Vehicle":[0,80],"trajectories":[1,59,142,164],"represent":[2],"an":[3,175],"essential":[4],"information":[5,33,44,195],"source":[6],"in":[7,60,143,162,196,212],"intelligent":[8,213],"transportation":[9,214],"systems.":[10],"Prior":[11],"trajectory":[12,99,184,210,223],"completion":[13],"models":[14],"based":[15],"on":[16,26,122,189],"Automatic":[17],"Number":[18],"Plate":[19],"Recognition":[20],"(ANPR)":[21],"data":[22,62,93,211],"have":[23,35,49,64],"typically":[24],"depended":[25],"vehicle":[27,67,141,190,209],"re-identification":[28,191],"results":[29,129],"or":[30,34],"road":[31,193],"network":[32,194],"employed":[36,131],"static":[37],"knowledge":[38,100,103,121,181],"graphs":[39,182],"to":[40,118,132,157,167],"integrate":[41],"the":[42,54,120,123,127,159,204,220],"two":[43],"sources.":[45],"However,":[46],"these":[47],"methods":[48],"not":[50],"taken":[51],"into":[52,96],"account":[53],"implicit":[55],"temporal":[56,98,113,180],"characteristics":[57],"of":[58,178,208,222],"ANPR":[61,92,144],"and":[63,115,125,150,170,192,206,227],"neglected":[65],"individual":[66],"preferences.":[68],"To":[69],"address":[70],"this":[71,73],"void,":[72],"study":[74],"proposes":[75],"a":[76,97,111],"Temporal":[77],"Knowledge":[78],"Graph-based":[79],"Trajectory":[81],"Completion":[82],"Model":[83],"(TKG-VTC).":[84],"The":[85],"model":[86,147],"implementation":[87,221],"comprises":[88],"three":[89],"stages:":[90],"first,":[91],"are":[94,130],"converted":[95],"graph;":[101,124],"second,":[102],"representation":[104],"learning":[105],"is":[106,155,200],"conducted":[107],"using":[108],"nontemporal":[109],"relations,":[110],"biased":[112],"regularizer":[114],"multivector":[116],"embeddings":[117],"embed":[119],"finally,":[126],"embedded":[128],"perform":[133],"link":[134],"prediction":[135],"for":[136,183,202],"incomplete":[137],"trajectories,":[138],"thereby":[139],"restoring":[140],"data.":[145],"Through":[146],"evaluation":[148],"metrics":[149],"dimensionality":[151],"reduction":[152],"experiments,":[153],"TKG-VTC":[154],"observed":[156],"demonstrate":[158],"best":[160],"performance":[161,205],"completing":[163],"when":[165],"compared":[166],"TComplEx,":[168],"TNTComplEx,":[169],"TeLM.":[171],"This":[172,199],"research":[173],"introduces":[174],"innovative":[176],"application":[177],"employing":[179],"reconstruction,":[185],"which":[186],"eliminates":[187],"dependence":[188],"previous":[197],"methodologies.":[198],"advantageous":[201],"enhancing":[203],"dependability":[207],"systems,":[215],"as":[216,218],"well":[217],"facilitating":[219],"prediction,":[224],"demand":[225],"analysis,":[226],"accident":[228],"warning":[229],"applications.":[230]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-17T09:09:15.849793","created_date":"2025-10-10T00:00:00"}