{"id":"https://openalex.org/W3201108447","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533443","title":"Online Anomalous Taxi Trajectory Detection Based on Multidimensional Criteria","display_name":"Online Anomalous Taxi Trajectory Detection Based on Multidimensional Criteria","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3201108447","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533443","mag":"3201108447"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533443","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533443","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","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/A5100677500","display_name":"Dongmei Chen","orcid":"https://orcid.org/0000-0002-9917-2536"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongmei Chen","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071781461","display_name":"Yang Du","orcid":"https://orcid.org/0000-0003-3012-0778"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Du","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084941663","display_name":"Shenghui Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shenghui Xu","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053110771","display_name":"Yu-E Sun","orcid":"https://orcid.org/0000-0002-0018-4810"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu-E Sun","raw_affiliation_strings":["School of Rail Transportation, Soochow University, Suzhou, China","Suzhou Institute for Advanced Study, University of Science and Technology of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Rail Transportation, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]},{"raw_affiliation_string":"Suzhou Institute for Advanced Study, University of Science and Technology of China, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101998852","display_name":"He Huang","orcid":"https://orcid.org/0000-0003-2768-6607"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He Huang","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China","Suzhou Institute for Advanced Study, University of Science and Technology of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]},{"raw_affiliation_string":"Suzhou Institute for Advanced Study, University of Science and Technology of China, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017276929","display_name":"Guoju Gao","orcid":"https://orcid.org/0000-0002-0104-8263"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoju Gao","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I3923682"],"apc_list":null,"apc_paid":null,"fwci":0.7326,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.73477175,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.8660631775856018},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7712835669517517},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6872732639312744},{"id":"https://openalex.org/keywords/false-positive-rate","display_name":"False positive rate","score":0.5420111417770386},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.4675509035587311},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4345451891422272},{"id":"https://openalex.org/keywords/false-discovery-rate","display_name":"False discovery rate","score":0.42758113145828247},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.4270170331001282},{"id":"https://openalex.org/keywords/false-positives-and-false-negatives","display_name":"False positives and false negatives","score":0.4220142066478729},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31142276525497437}],"concepts":[{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.8660631775856018},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7712835669517517},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6872732639312744},{"id":"https://openalex.org/C95922358","wikidata":"https://www.wikidata.org/wiki/Q5432725","display_name":"False positive rate","level":2,"score":0.5420111417770386},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.4675509035587311},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4345451891422272},{"id":"https://openalex.org/C193244246","wikidata":"https://www.wikidata.org/wiki/Q5432696","display_name":"False discovery rate","level":3,"score":0.42758113145828247},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.4270170331001282},{"id":"https://openalex.org/C112789634","wikidata":"https://www.wikidata.org/wiki/Q18207010","display_name":"False positives and false negatives","level":3,"score":0.4220142066478729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31142276525497437},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533443","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533443","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1968701380","https://openalex.org/W2046466133","https://openalex.org/W2091770595","https://openalex.org/W2126194848","https://openalex.org/W2136975357","https://openalex.org/W2168884627","https://openalex.org/W2293117569","https://openalex.org/W2296719434","https://openalex.org/W2484357102","https://openalex.org/W2514056879","https://openalex.org/W2601893308","https://openalex.org/W2767297659","https://openalex.org/W2904970799","https://openalex.org/W2912986282","https://openalex.org/W2914166707","https://openalex.org/W2941833720","https://openalex.org/W2982321152","https://openalex.org/W3029191757","https://openalex.org/W3032453802","https://openalex.org/W3080262031","https://openalex.org/W3134624922","https://openalex.org/W6775845573","https://openalex.org/W6778338457"],"related_works":["https://openalex.org/W1991225657","https://openalex.org/W4292605373","https://openalex.org/W2020413892","https://openalex.org/W2951146195","https://openalex.org/W3123215897","https://openalex.org/W3119537175","https://openalex.org/W2810356275","https://openalex.org/W2027184711","https://openalex.org/W2102122784","https://openalex.org/W2093463665"],"abstract_inverted_index":{"Online":[0],"anomalous":[1,30,120,128,133],"taxi":[2,10,168],"trajectory":[3,121,129],"detection,":[4],"which":[5],"identifies":[6],"anomalies":[7,138],"from":[8,36,171],"ongoing":[9],"trajectories,":[11],"has":[12],"become":[13],"an":[14,118],"important":[15],"and":[16,46,60,102,191],"fundamental":[17],"concern":[18],"in":[19,185],"many":[20,74],"real-world":[21,167],"applications.":[22],"Most":[23],"of":[24,39,57,63,187],"the":[25,29,33,37,49,55,61,147,151,161,166],"existing":[26],"studies":[27],"define":[28],"trajectories":[31,134],"as":[32,77],"ones":[34],"deviating":[35],"majority":[38],"routes":[40,76],"or":[41],"showing":[42],"abnormal":[43],"driving":[44],"time":[45],"distance":[47],"at":[48,146],"same":[50,148],"time.":[51],"However,":[52],"due":[53],"to":[54,93,99,107,131],"complexity":[56],"road":[58],"conditions":[59],"variety":[62],"passenger":[64],"preferences,":[65],"those":[66],"methods":[67,184],"have":[68],"large":[69],"false-positive":[70,81,192],"rates,":[71],"i.e.,":[72],"reporting":[73],"normal":[75,100],"anomalies.":[78],"A":[79],"high":[80],"rate":[82],"is":[83],"harmful":[84],"since":[85],"false":[86,152,156],"alarms":[87],"will":[88],"1)":[89],"bring":[90],"unnecessary":[91],"panic":[92],"passengers,":[94],"2)":[95],"cause":[96],"fiscally":[97],"punishments":[98],"drivers,":[101],"3)":[103],"wastes":[104],"human":[105],"resource":[106],"deal":[108],"with":[109],"drivers'":[110],"complaints.":[111],"To":[112],"this":[113,115],"end,":[114],"paper":[116],"proposes":[117],"online":[119],"detection":[122],"method,":[123],"namely":[124],"multidimensional":[125,141],"criteria":[126,142],"based":[127,164],"(MCAT),":[130],"identify":[132],"online.":[135],"It":[136],"judges":[137],"by":[139],"considering":[140],"(similarity,":[143],"time,":[144,149],"distance)":[145],"reducing":[150],"positives":[153],"without":[154],"sacrificing":[155],"negative":[157],"rates.":[158],"We":[159],"evaluate":[160],"proposed":[162],"method":[163,180],"on":[165],"data":[169],"collected":[170],"Shanghai,":[172],"China.":[173],"The":[174],"experimental":[175],"results":[176],"demonstrate":[177],"that":[178],"our":[179],"can":[181],"outperform":[182],"state-of-the-art":[183],"terms":[186],"accuracy,":[188],"false-negative":[189],"rate,":[190],"rate.":[193]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}