{"id":"https://openalex.org/W2783937577","doi":"https://doi.org/10.1109/bigdata.2017.8258039","title":"BTCI: A new framework for identifying congestion cascades using bus trajectory data","display_name":"BTCI: A new framework for identifying congestion cascades using bus trajectory data","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2783937577","doi":"https://doi.org/10.1109/bigdata.2017.8258039","mag":"2783937577"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2017.8258039","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5024176415","display_name":"Meng-Fen Chiang","orcid":null},"institutions":[{"id":"https://openalex.org/I79891267","display_name":"Singapore Management University","ror":"https://ror.org/050qmg959","country_code":"SG","type":"education","lineage":["https://openalex.org/I79891267"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Meng-Fen Chiang","raw_affiliation_strings":["Living Analytics Research Centre, Singapore Management University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Living Analytics Research Centre, Singapore Management University, Singapore","institution_ids":["https://openalex.org/I79891267"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039617569","display_name":"Ee\u2010Peng Lim","orcid":"https://orcid.org/0000-0003-0065-8665"},"institutions":[{"id":"https://openalex.org/I79891267","display_name":"Singapore Management University","ror":"https://ror.org/050qmg959","country_code":"SG","type":"education","lineage":["https://openalex.org/I79891267"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Ee-Peng Lim","raw_affiliation_strings":["Living Analytics Research Centre, Singapore Management University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Living Analytics Research Centre, Singapore Management University, Singapore","institution_ids":["https://openalex.org/I79891267"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091716232","display_name":"Wang-Chien Lee","orcid":"https://orcid.org/0000-0002-8949-489X"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wang-Chien Lee","raw_affiliation_strings":["Department of Computer Science and Engineering, The Pennsylvania State University, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Pennsylvania State University, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070260406","display_name":"Agus T. Kwee","orcid":null},"institutions":[{"id":"https://openalex.org/I79891267","display_name":"Singapore Management University","ror":"https://ror.org/050qmg959","country_code":"SG","type":"education","lineage":["https://openalex.org/I79891267"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Agus Trisnajaya Kwee","raw_affiliation_strings":["Living Analytics Research Centre, Singapore Management University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Living Analytics Research Centre, Singapore Management University, Singapore","institution_ids":["https://openalex.org/I79891267"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0069,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.86213397,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1133","last_page":"1142"},"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/T10698","display_name":"Transportation Planning and Optimization","score":0.983299970626831,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.974399983882904,"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":0.7114510536193848},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.6827648282051086},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6084400415420532},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5379735827445984},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48174241185188293},{"id":"https://openalex.org/keywords/network-congestion","display_name":"Network congestion","score":0.46506598591804504},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.44062674045562744},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.26487499475479126},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.1968492865562439},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14491117000579834},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13226953148841858},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12183493375778198}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7114510536193848},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.6827648282051086},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6084400415420532},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5379735827445984},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48174241185188293},{"id":"https://openalex.org/C195563490","wikidata":"https://www.wikidata.org/wiki/Q180368","display_name":"Network congestion","level":3,"score":0.46506598591804504},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.44062674045562744},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.26487499475479126},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.1968492865562439},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14491117000579834},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13226953148841858},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12183493375778198},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata.2017.8258039","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:ink.library.smu.edu.sg:sis_research-4973","is_oa":false,"landing_page_url":"https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=4973&context=sis_research","pdf_url":null,"source":{"id":"https://openalex.org/S4306401925","display_name":"Singapore Management University Institutional Knowledge (InK) (Singapore Management University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79891267","host_organization_name":"Singapore Management University","host_organization_lineage":["https://openalex.org/I79891267"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://doi.org/10.1109/BigData.2017.8258039","raw_type":"Conference Proceeding Article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320320709","display_name":"National Research Foundation Singapore","ror":"https://ror.org/03cpyc314"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1514578609","https://openalex.org/W1660133578","https://openalex.org/W1978203369","https://openalex.org/W1989597542","https://openalex.org/W1996543006","https://openalex.org/W1999110238","https://openalex.org/W1999432478","https://openalex.org/W2020805267","https://openalex.org/W2025023381","https://openalex.org/W2034258124","https://openalex.org/W2044400205","https://openalex.org/W2048250993","https://openalex.org/W2073459066","https://openalex.org/W2075192215","https://openalex.org/W2117618130","https://openalex.org/W2118020555","https://openalex.org/W2132368295","https://openalex.org/W2154206668","https://openalex.org/W2165515835","https://openalex.org/W2168791259","https://openalex.org/W2294723619","https://openalex.org/W2296704245","https://openalex.org/W6637052001","https://openalex.org/W6668990524"],"related_works":["https://openalex.org/W4323768008","https://openalex.org/W3131574667","https://openalex.org/W4248382324","https://openalex.org/W4360995134","https://openalex.org/W2387529410","https://openalex.org/W2039473718","https://openalex.org/W3023605104","https://openalex.org/W2383578611","https://openalex.org/W2987583674","https://openalex.org/W2756388381"],"abstract_inverted_index":{"The":[0,66,92],"knowledge":[1],"of":[2,23,46,55,89,115,160],"traffic":[3,14,24,40,104,175],"health":[4,41],"status":[5,42],"is":[6,143],"essential":[7],"to":[8,85],"the":[9,38,139,150,165,174],"general":[10],"public":[11],"and":[12,43,62,76,112,163,177],"urban":[13],"management.":[15],"To":[16],"identify":[17,135],"congestion":[18,47,63,90,101,105,136,141,167],"cascades,":[19,137],"an":[20],"important":[21],"phenomenon":[22],"health,":[25],"we":[26],"propose":[27],"a":[28,78,87,119],"Bus":[29],"Trajectory":[30],"based":[31],"Congestion":[32],"Identification":[33],"(BTCI)":[34],"framework":[35],"that":[36,130],"explores":[37],"anomalous":[39],"structure":[44],"properties":[45],"cascades":[48,64,106,168],"using":[49],"bus":[50,126],"trajectory":[51,127],"data.":[52],"BTCI":[53,132],"consists":[54],"two":[56],"main":[57],"steps,":[58],"congested":[59,95,116,147],"segment":[60],"extraction":[61],"identification.":[65],"former":[67],"constructs":[68],"path":[69],"speed":[70,182],"models":[71],"from":[72],"historical":[73],"vehicle":[74,181],"transitions":[75],"design":[77],"non-parametric":[79],"Kernel":[80],"Density":[81],"Estimation":[82],"(KDE)":[83],"function":[84],"derive":[86],"measure":[88],"score.":[91],"latter":[93],"aggregates":[94],"segments":[96,117],"(i.e.,":[97],"those":[98],"with":[99,173,180],"high":[100],"scores)":[102],"into":[103],"by":[107],"unifying":[108],"both":[109],"attribute":[110],"coherence":[111],"spatio-temporal":[113],"closeness":[114],"within":[118],"cascade.":[120],"Extensive":[121],"evaluations":[122],"on":[123],"11.8":[124],"million":[125],"data":[128],"show":[129],"(1)":[131],"can":[133],"effectively":[134],"(2)":[138],"proposed":[140,151],"score":[142],"effective":[144],"in":[145,158],"extracting":[146],"segments,":[148],"(3)":[149],"unified":[152],"approach":[153],"significantly":[154],"outperforms":[155],"alternative":[156],"approaches":[157],"terms":[159],"extended":[161],"precision,":[162],"(4)":[164],"identified":[166],"are":[169],"realistic,":[170],"matching":[171],"well":[172],"news":[176],"highly":[178],"correlated":[179],"bands.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}