{"id":"https://openalex.org/W4379805280","doi":"https://doi.org/10.1109/tits.2023.3279321","title":"HRST-LR: A Hessian Regularization Spatio-Temporal Low Rank Algorithm for Traffic Data Imputation","display_name":"HRST-LR: A Hessian Regularization Spatio-Temporal Low Rank Algorithm for Traffic Data Imputation","publication_year":2023,"publication_date":"2023-06-08","ids":{"openalex":"https://openalex.org/W4379805280","doi":"https://doi.org/10.1109/tits.2023.3279321"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2023.3279321","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2023.3279321","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transactions on Intelligent Transportation Systems","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/A5065313978","display_name":"Xiuqin Xu","orcid":"https://orcid.org/0000-0001-6639-5269"},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuqin Xu","raw_affiliation_strings":["School of Mathematics and Statistics, Fujian Normal University, Fujian, China"],"raw_orcid":"https://orcid.org/0000-0001-6639-5269","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Fujian Normal University, Fujian, China","institution_ids":["https://openalex.org/I111753288"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101851003","display_name":"Ming\u2010Wei Lin","orcid":"https://orcid.org/0000-0003-2026-7178"},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingwei Lin","raw_affiliation_strings":["College of Computer and Cyber Security, Fujian Normal University, Fujian, China"],"raw_orcid":"https://orcid.org/0000-0003-2026-7178","affiliations":[{"raw_affiliation_string":"College of Computer and Cyber Security, Fujian Normal University, Fujian, China","institution_ids":["https://openalex.org/I111753288"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088955392","display_name":"Xin Luo","orcid":"https://orcid.org/0000-0002-1348-5305"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Luo","raw_affiliation_strings":["College of Computer and Information Science, Southwest University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-1348-5305","affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100437308","display_name":"Zeshui Xu","orcid":"https://orcid.org/0000-0003-3547-2908"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zeshui Xu","raw_affiliation_strings":["Business School, Sichuan University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-3547-2908","affiliations":[{"raw_affiliation_string":"Business School, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":11.1809,"has_fulltext":false,"cited_by_count":100,"citation_normalized_percentile":{"value":0.99528089,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"24","issue":"10","first_page":"11001","last_page":"11017"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9958999752998352,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9919000267982483,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.6093452572822571},{"id":"https://openalex.org/keywords/hessian-matrix","display_name":"Hessian matrix","score":0.6087662577629089},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5884584784507751},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5118852853775024},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.45684918761253357},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4328274130821228},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2814156413078308},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20538973808288574},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20401430130004883}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6093452572822571},{"id":"https://openalex.org/C203616005","wikidata":"https://www.wikidata.org/wiki/Q620495","display_name":"Hessian matrix","level":2,"score":0.6087662577629089},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5884584784507751},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5118852853775024},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.45684918761253357},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4328274130821228},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2814156413078308},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20538973808288574},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20401430130004883},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2023.3279321","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2023.3279321","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G187774861","display_name":null,"funder_award_id":"2022J06020","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"},{"id":"https://openalex.org/G5310342163","display_name":null,"funder_award_id":"62272103","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G804834654","display_name":"HDD/SSD\u6df7\u5408\u5b58\u50a8\u7cfb\u7edf\u7684\u6570\u636e\u5e03\u5c40\u548c\u7f13\u5b58\u7ba1\u7406\u7b56\u7565\u7814\u7a76","funder_award_id":"61872086","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8515641209","display_name":null,"funder_award_id":"62272078","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"},{"id":"https://openalex.org/F4320321878","display_name":"Natural Science Foundation of Fujian Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W1492095519","https://openalex.org/W1565746575","https://openalex.org/W1606533552","https://openalex.org/W1798398164","https://openalex.org/W1860736741","https://openalex.org/W1974573780","https://openalex.org/W1978346123","https://openalex.org/W1990069825","https://openalex.org/W2060204507","https://openalex.org/W2065383359","https://openalex.org/W2075547019","https://openalex.org/W2091449379","https://openalex.org/W2106221905","https://openalex.org/W2108119513","https://openalex.org/W2117368434","https://openalex.org/W2117898853","https://openalex.org/W2118718620","https://openalex.org/W2135029798","https://openalex.org/W2156718197","https://openalex.org/W2165991108","https://openalex.org/W2184263948","https://openalex.org/W2307933510","https://openalex.org/W2405400056","https://openalex.org/W2606637053","https://openalex.org/W2611328865","https://openalex.org/W2737032940","https://openalex.org/W2760130459","https://openalex.org/W2803805253","https://openalex.org/W2810798422","https://openalex.org/W2901144993","https://openalex.org/W2902776372","https://openalex.org/W2904957802","https://openalex.org/W2919538836","https://openalex.org/W2923144060","https://openalex.org/W2928382658","https://openalex.org/W2930208852","https://openalex.org/W2933911887","https://openalex.org/W2981601811","https://openalex.org/W2989870471","https://openalex.org/W2996451395","https://openalex.org/W3004529643","https://openalex.org/W3028956410","https://openalex.org/W3043567704","https://openalex.org/W3069326598","https://openalex.org/W3094071795","https://openalex.org/W3102415113","https://openalex.org/W3110116780","https://openalex.org/W3129938072","https://openalex.org/W3134651463","https://openalex.org/W3140898540","https://openalex.org/W3176211171","https://openalex.org/W3202635391","https://openalex.org/W3205590958","https://openalex.org/W3212797624","https://openalex.org/W4214827269","https://openalex.org/W4224442581","https://openalex.org/W4285130767","https://openalex.org/W4287062502","https://openalex.org/W4315777794","https://openalex.org/W4393773530","https://openalex.org/W6636206708","https://openalex.org/W6669355818","https://openalex.org/W6677329495","https://openalex.org/W6677759377","https://openalex.org/W6680012447","https://openalex.org/W6682755970","https://openalex.org/W6752046673","https://openalex.org/W6840585966"],"related_works":["https://openalex.org/W2611031068","https://openalex.org/W1704347466","https://openalex.org/W4283017538","https://openalex.org/W1996936972","https://openalex.org/W1545275724","https://openalex.org/W2802707792","https://openalex.org/W2075777916","https://openalex.org/W3021699548","https://openalex.org/W2800988248","https://openalex.org/W4385064145"],"abstract_inverted_index":{"Intelligent":[0],"Transportation":[1],"Systems":[2],"(ITSs)":[3],"are":[4,29],"vital":[5],"for":[6,144,184,237],"alleviating":[7],"traffic":[8,12,27,43,55,106,142,191,197,210,238],"congestion":[9],"and":[10,21,50,86,101,161],"improving":[11],"efficiency.":[13],"Due":[14],"to":[15,70,74,79,96],"the":[16,37,90,98,137,151,164,178,186,190,208,214,225,231,242],"delay":[17],"of":[18,23,39,53,83,140,158,167,244],"network":[19,107],"transmission":[20],"failure":[22],"detectors,":[24],"massive":[25],"missing":[26,54,209,226],"data":[28,56,198,211,239],"often":[30,220],"produced":[31],"in":[32,41,105,110,189,207],"ITSs,":[33],"which":[34],"evidently":[35],"decreases":[36],"accuracy":[38],"decision-making":[40],"road":[42,168,182],"management.":[44],"Hence,":[45,230],"how":[46],"establishing":[47],"a":[48,58,120,141,155,171],"precise":[49],"efficient":[51],"estimation":[52,112,212],"becomes":[57],"hot":[59],"yet":[60],"thorny":[61],"issue.":[62],"Low-rank":[63],"matrix":[64,143],"completion":[65],"(LR-MC)":[66],"model":[67,97],"has":[68],"proven":[69],"be":[71],"highly":[72,235],"effective":[73],"address":[75],"this":[76,117],"issue":[77],"owing":[78],"its":[80,147],"fine":[81],"representativeness":[82],"such":[84],"high-dimensional":[85],"incomplete":[87],"data.":[88,192],"However,":[89],"existing":[91],"LR-MC":[92],"models":[93],"mostly":[94],"fail":[95],"inherently":[99],"temporal":[100,152],"spatial":[102,174,187],"correlations":[103],"hidden":[104],"structure,":[108,148],"resulting":[109],"low":[111,124],"accuracy.":[113],"To":[114],"improve":[115],"it,":[116],"paper":[118],"proposes":[119],"Hessian":[121,172],"regularization":[122,173],"spatio-temporal":[123,246],"rank":[125],"(HRST-LR)":[126],"algorithm":[127,233],"with":[128,213,241],"three":[129],"main-fold":[130],"ideas:":[131],"a)":[132],"imposing":[133],"low-rank":[134,247],"property":[135],"into":[136],"global":[138],"features":[139],"precisely":[145],"learning":[146],"b)":[149],"capturing":[150],"evolvement":[153],"via":[154],"second-order":[156],"difference":[157],"time-series":[159],"constraint,":[160,175],"c)":[162],"modeling":[163],"similar":[165],"space":[166],"segments":[169,183],"through":[170],"thus":[176],"exploring":[177],"local":[179],"correlation":[180],"between":[181],"representing":[185],"patterns":[188],"Experimental":[193],"results":[194],"on":[195],"four":[196],"sets":[199],"prove":[200],"that":[201],"HRST-LR":[202,232],"outperforms":[203],"several":[204],"state-of-the-art":[205],"methods":[206],"root":[215],"mean":[216],"squared":[217],"error":[218],"improvements":[219],"higher":[221],"than":[222],"14%":[223],"when":[224],"rate":[227],"is":[228,234],"90%.":[229],"valuable":[236],"imputation":[240],"need":[243],"performing":[245],"analysis.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":34},{"year":2024,"cited_by_count":56},{"year":2023,"cited_by_count":5}],"updated_date":"2026-07-25T15:57:00.446498","created_date":"2025-10-10T00:00:00"}