{"id":"https://openalex.org/W4404520614","doi":"https://doi.org/10.1109/jiot.2024.3502517","title":"CLGSDN: Contrastive-Learning-Based Graph Structure Denoising Network for Traffic Prediction","display_name":"CLGSDN: Contrastive-Learning-Based Graph Structure Denoising Network for Traffic Prediction","publication_year":2024,"publication_date":"2024-11-19","ids":{"openalex":"https://openalex.org/W4404520614","doi":"https://doi.org/10.1109/jiot.2024.3502517"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2024.3502517","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3502517","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Internet of Things Journal","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/A5100416334","display_name":"Peng Peng","orcid":"https://orcid.org/0000-0003-2838-2111"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"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":"Peng Peng","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100736156","display_name":"Xuewen Chen","orcid":"https://orcid.org/0000-0002-2794-3987"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"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":false,"raw_author_name":"Xuewen Chen","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100441861","display_name":"Xudong Zhang","orcid":"https://orcid.org/0000-0003-1896-4898"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"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":false,"raw_author_name":"Xudong Zhang","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110364708","display_name":"Haina Tang","orcid":"https://orcid.org/0000-0002-7150-0243"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"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":false,"raw_author_name":"Haina Tang","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103865094","display_name":"Hanji Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210108629","display_name":"Computer Network Information Center","ror":"https://ror.org/01s0wyf50","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210108629"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanji Shen","raw_affiliation_strings":["Computer Network Information Center, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Computer Network Information Center, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210108629","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100361625","display_name":"Jun Li","orcid":"https://orcid.org/0000-0001-5845-8602"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210108629","display_name":"Computer Network Information Center","ror":"https://ror.org/01s0wyf50","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210108629"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Li","raw_affiliation_strings":["Computer Network Information Center, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Computer Network Information Center, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210108629","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100416334"],"corresponding_institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":1.959,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.89029049,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"12","issue":"7","first_page":"8638","last_page":"8652"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.9552000164985657,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.9552000164985657,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"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":0.789408802986145},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5620507001876831},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.42457157373428345},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4142873287200928},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3543820381164551},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3255871534347534},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.22952646017074585}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.789408802986145},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5620507001876831},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.42457157373428345},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4142873287200928},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3543820381164551},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3255871534347534},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.22952646017074585}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2024.3502517","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3502517","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1262453860","display_name":null,"funder_award_id":"52071312","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":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W2064675550","https://openalex.org/W2528639018","https://openalex.org/W2530386080","https://openalex.org/W2626818931","https://openalex.org/W2756203131","https://openalex.org/W2897157818","https://openalex.org/W2903871660","https://openalex.org/W2907492528","https://openalex.org/W2950635152","https://openalex.org/W2963017945","https://openalex.org/W2965341826","https://openalex.org/W2966398094","https://openalex.org/W2996847713","https://openalex.org/W3035467734","https://openalex.org/W3036446966","https://openalex.org/W3039075121","https://openalex.org/W3116239416","https://openalex.org/W3123191313","https://openalex.org/W3125675327","https://openalex.org/W3153206160","https://openalex.org/W3174022889","https://openalex.org/W3178384248","https://openalex.org/W3201412947","https://openalex.org/W4224931678","https://openalex.org/W4290877193","https://openalex.org/W4309651348","https://openalex.org/W4311926226","https://openalex.org/W4312266488","https://openalex.org/W4312703862","https://openalex.org/W4320009860","https://openalex.org/W4320015890","https://openalex.org/W4367046748","https://openalex.org/W4367595602","https://openalex.org/W4381326995","https://openalex.org/W4381786098","https://openalex.org/W4382203390","https://openalex.org/W4382239590","https://openalex.org/W4382318032","https://openalex.org/W4382449675","https://openalex.org/W4384518457","https://openalex.org/W4385245566","https://openalex.org/W4392543778","https://openalex.org/W6719270105","https://openalex.org/W6726873649","https://openalex.org/W6745537798","https://openalex.org/W6746015598","https://openalex.org/W6760886919","https://openalex.org/W6771932116","https://openalex.org/W6772384842","https://openalex.org/W6779462361","https://openalex.org/W6780221082","https://openalex.org/W6784694379","https://openalex.org/W6791375057","https://openalex.org/W6810650646","https://openalex.org/W6862434374"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W2033914206"],"abstract_inverted_index":{"The":[0,126,180],"graph":[1,34,77,83,92,116,122,144,164,173],"neural":[2],"network-based":[3],"prediction":[4,51,191],"models":[5,192],"have":[6],"demonstrated":[7],"remarkable":[8],"utility":[9],"in":[10,137,177],"traffic":[11,50,148,178,190,212],"prediction,":[12],"and":[13,63,105,154,166,196,215],"their":[14],"efficacy":[15],"is":[16,28,130],"highly":[17],"determined":[18],"by":[19,158,193],"the":[20,23,43,56,91,101,120,138,143,163],"quality":[21],"of":[22,58,115,162,209],"provided":[24],"graphs.":[25,44,198],"Consequently,":[26],"there":[27],"an":[29],"increasing":[30],"demand":[31],"for":[32,49,132,205],"employing":[33],"structure":[35,84],"learning":[36,133,175],"(GSL)":[37],"techniques":[38,48],"to":[39,111,145,170],"optimize":[40],"or":[41],"generate":[42,112],"However,":[45],"existing":[46],"GSL":[47],"encounter":[52],"various":[53],"issues,":[54],"including":[55,211],"absence":[57],"temporal":[59],"dynamicity,":[60],"noisy":[61,156],"connections,":[62],"insufficient":[64],"supervisory":[65],"information.":[66],"To":[67],"address":[68],"these":[69],"limitations,":[70],"this":[71],"article":[72],"proposes":[73],"a":[74,96,113,206],"novel":[75],"two-stage":[76],"generation":[78,93],"framework":[79,89],"called":[80],"contrastive":[81,174],"learning-based":[82],"denoising":[85],"network":[86],"(CLGSDN).":[87],"This":[88],"formulates":[90],"task":[94],"as":[95],"probabilistic":[97],"observation-inference":[98],"process:":[99],"using":[100],"self-learning":[102,127],"adjacency":[103,128],"matrix":[104,129],"time":[106],"delayed":[107],"self-attention":[108],"(TDSA)":[109],"methods":[110],"series":[114],"observations,":[117],"then":[118],"inferring":[119],"optimal":[121],"based":[123],"on":[124],"observations.":[125],"responsible":[131],"all":[134],"potential":[135],"connections":[136,157],"graph,":[139],"while":[140],"TDSA":[141],"enables":[142],"change":[146],"with":[147],"flow.":[149],"In":[150],"addition,":[151],"CLGSDN":[152,185],"identifies":[153],"eliminates":[155],"modeling":[159],"negative":[160],"samples":[161],"(edges),":[165],"defines":[167],"virtual":[168],"labels":[169],"achieve":[171],"spatiotemporal":[172],"(ST-GCL)":[176],"prediction.":[179],"experimental":[181],"results":[182],"show":[183],"that":[184],"significantly":[186],"enhances":[187],"current":[188],"mainstream":[189],"providing":[194],"reliable":[195],"efficient":[197],"As":[199],"such,":[200],"it":[201],"has":[202],"significant":[203],"implications":[204],"wide":[207],"range":[208],"applications,":[210],"management,":[213],"logistics,":[214],"smart":[216],"transportation":[217],"systems.":[218]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
