{"id":"https://openalex.org/W2343462218","doi":"https://doi.org/10.1109/tits.2015.2507259","title":"Matrix and Tensor Based Methods for Missing Data Estimation in Large Traffic Networks","display_name":"Matrix and Tensor Based Methods for Missing Data Estimation in Large Traffic Networks","publication_year":2016,"publication_date":"2016-01-18","ids":{"openalex":"https://openalex.org/W2343462218","doi":"https://doi.org/10.1109/tits.2015.2507259","mag":"2343462218"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2015.2507259","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2015.2507259","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/A5109489129","display_name":"Muhammad Tayyab Asif","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Muhammad Tayyab Asif","raw_affiliation_strings":["School of Electrical and Electronic Engineering, College of Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, College of Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086550237","display_name":"Nikola Mitrovi\u0107","orcid":"https://orcid.org/0000-0002-5057-848X"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Nikola Mitrovic","raw_affiliation_strings":["School of Electrical and Electronic Engineering, College of Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, College of Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082613025","display_name":"Justin Dauwels","orcid":"https://orcid.org/0000-0002-4390-1568"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Justin Dauwels","raw_affiliation_strings":["School of Electrical and Electronic Engineering, College of Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, College of Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109246810","display_name":"Patrick Jaillet","orcid":"https://orcid.org/0000-0002-8585-6566"},"institutions":[{"id":"https://openalex.org/I4210167254","display_name":"Singapore-MIT Alliance for Research and Technology","ror":"https://ror.org/05yb3w112","country_code":"SG","type":"education","lineage":["https://openalex.org/I4210167254"]},{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["SG","US"],"is_corresponding":false,"raw_author_name":"Patrick Jaillet","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, School of Engineering, Singapore-Massachusetts Institute of Technology Alliance for Research and Technology, Cambridge, MA, Singapore"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, School of Engineering, Singapore-Massachusetts Institute of Technology Alliance for Research and Technology, Cambridge, MA, Singapore","institution_ids":["https://openalex.org/I4210167254","https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5109489129"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":15.0697,"has_fulltext":false,"cited_by_count":158,"citation_normalized_percentile":{"value":0.99358597,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"17","issue":"7","first_page":"1816","last_page":"1825"},"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":0.9902999997138977,"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/T12303","display_name":"Tensor decomposition and applications","score":0.9758999943733215,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.7341192960739136},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.7120724320411682},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6202752590179443},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6168544292449951},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5237880945205688},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.512370228767395},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.47054487466812134},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4451354444026947},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4323290288448334},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40498673915863037},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3406873941421509},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3146507740020752},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27484968304634094},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1814153790473938},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.1596953272819519}],"concepts":[{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.7341192960739136},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.7120724320411682},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6202752590179443},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6168544292449951},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5237880945205688},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.512370228767395},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.47054487466812134},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4451354444026947},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4323290288448334},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40498673915863037},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3406873941421509},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3146507740020752},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27484968304634094},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1814153790473938},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.1596953272819519},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2015.2507259","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2015.2507259","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":[{"display_name":"Sustainable cities and communities","score":0.7900000214576721,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320765","display_name":"Singapore-MIT Alliance for Research and Technology Centre","ror":"https://ror.org/05yb3w112"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W271314235","https://openalex.org/W564911087","https://openalex.org/W1798398164","https://openalex.org/W1814521481","https://openalex.org/W1920010643","https://openalex.org/W1974539152","https://openalex.org/W1979058395","https://openalex.org/W1981392829","https://openalex.org/W1984899043","https://openalex.org/W1989797507","https://openalex.org/W1991770012","https://openalex.org/W2004891103","https://openalex.org/W2005530058","https://openalex.org/W2011359124","https://openalex.org/W2020641160","https://openalex.org/W2024165284","https://openalex.org/W2026561823","https://openalex.org/W2033903280","https://openalex.org/W2039417141","https://openalex.org/W2049500727","https://openalex.org/W2051299429","https://openalex.org/W2058252247","https://openalex.org/W2059941999","https://openalex.org/W2060207181","https://openalex.org/W2066016439","https://openalex.org/W2078104845","https://openalex.org/W2096532744","https://openalex.org/W2100782160","https://openalex.org/W2118550318","https://openalex.org/W2128287406","https://openalex.org/W2153811040","https://openalex.org/W2153919224","https://openalex.org/W2163150789","https://openalex.org/W2165992156","https://openalex.org/W2171959453","https://openalex.org/W2541565311","https://openalex.org/W2611328865","https://openalex.org/W6615544320","https://openalex.org/W6640122379"],"related_works":["https://openalex.org/W2782904003","https://openalex.org/W4226434912","https://openalex.org/W2118633810","https://openalex.org/W2150953077","https://openalex.org/W4292636185","https://openalex.org/W2002598339","https://openalex.org/W2050785904","https://openalex.org/W2920931670","https://openalex.org/W2136348949","https://openalex.org/W1995410415"],"abstract_inverted_index":{"Intelligent":[0],"transportation":[1],"systems":[2],"(ITSs)":[3],"gather":[4],"information":[5],"about":[6],"traffic":[7,72,81],"conditions":[8],"by":[9,38,69,147],"collecting":[10],"data":[11,21,32,49,141],"from":[12,24],"a":[13,34],"wide":[14],"range":[15],"of":[16,47,86,117,121,130,135,139],"on-ground":[17],"sensors.":[18],"The":[19],"collected":[20],"usually":[22],"suffer":[23],"irregular":[25],"spatial":[26],"and":[27,52,60,103,143],"temporal":[28],"resolution.":[29],"Consequently,":[30],"missing":[31,48,67,87],"is":[33,119],"common":[35,71],"problem":[36,46],"faced":[37],"ITSs.":[39],"In":[40],"this":[41],"paper,":[42],"we":[43,89,111],"consider":[44,112],"the":[45,84,128,140,144],"in":[50,74,83,133],"large":[51,75],"diverse":[53],"road":[54,76,114,124],"networks.":[55,77],"We":[56,126],"propose":[57],"various":[58],"matrix":[59],"tensor":[61],"based":[62],"methods":[63,132],"to":[64],"estimate":[65],"these":[66,80,131,148],"values":[68],"extracting":[70],"patterns":[73,82],"To":[78],"obtain":[79],"presence":[85],"data,":[88],"apply":[90],"fixed-point":[91],"continuation":[92],"with":[93],"approximate":[94],"singular":[95],"value":[96],"decomposition,":[97,100],"canonical":[98],"polyadic":[99],"least":[101],"squares,":[102],"variational":[104],"Bayesian":[105],"principal":[106],"component":[107],"analysis.":[108],"For":[109],"analysis,":[110],"different":[113],"networks,":[115],"each":[116],"which":[118],"composed":[120],"around":[122],"1500":[123],"segments.":[125],"evaluate":[127],"performance":[129],"terms":[134],"estimation":[136],"accuracy,":[137],"variance":[138],"set,":[142],"bias":[145],"imparted":[146],"methods.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":21},{"year":2021,"cited_by_count":20},{"year":2020,"cited_by_count":19},{"year":2019,"cited_by_count":17},{"year":2018,"cited_by_count":19},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
