{"id":"https://openalex.org/W2903859792","doi":"https://doi.org/10.1109/itsc.2018.8569015","title":"Real-Time Taxi Demand Prediction using data from the web","display_name":"Real-Time Taxi Demand Prediction using data from the web","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2903859792","doi":"https://doi.org/10.1109/itsc.2018.8569015","mag":"2903859792"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2018.8569015","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2018.8569015","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 21st International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-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/A5012755517","display_name":"Ioulia Markou","orcid":"https://orcid.org/0000-0002-3261-4176"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":true,"raw_author_name":"Ioulia Markou","raw_affiliation_strings":["Department of Management Engineering, Technical University of Denmark (DTU)"],"affiliations":[{"raw_affiliation_string":"Department of Management Engineering, Technical University of Denmark (DTU)","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078981714","display_name":"Filipe Rodrigues","orcid":"https://orcid.org/0000-0001-6979-6498"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Filipe Rodrigues","raw_affiliation_strings":["Department of Management Engineering, Technical University of Denmark (DTU)"],"affiliations":[{"raw_affiliation_string":"Department of Management Engineering, Technical University of Denmark (DTU)","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001424439","display_name":"Francisco C. Pereira","orcid":"https://orcid.org/0000-0001-5457-9909"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Francisco C. Pereira","raw_affiliation_strings":["Department of Management Engineering, Technical University of Denmark (DTU)"],"affiliations":[{"raw_affiliation_string":"Department of Management Engineering, Technical University of Denmark (DTU)","institution_ids":["https://openalex.org/I96673099"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012755517"],"corresponding_institution_ids":["https://openalex.org/I96673099"],"apc_list":null,"apc_paid":null,"fwci":1.749,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.84774308,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1664","last_page":"1671"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9995999932289124,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9990000128746033,"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":0.7436773180961609},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6934003829956055},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6610627174377441},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6557894945144653},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5815070867538452},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.537472665309906},{"id":"https://openalex.org/keywords/mean-absolute-percentage-error","display_name":"Mean absolute percentage error","score":0.4782927632331848},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.46513834595680237},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.4447614252567291},{"id":"https://openalex.org/keywords/real-time-data","display_name":"Real-time data","score":0.4420422613620758},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.4289504289627075},{"id":"https://openalex.org/keywords/concept-drift","display_name":"Concept drift","score":0.4211128354072571},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4201250970363617},{"id":"https://openalex.org/keywords/unstructured-data","display_name":"Unstructured data","score":0.4120887815952301},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40141531825065613},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39779698848724365},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3856322169303894},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34874868392944336},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.22108468413352966},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.12261819839477539},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.11937502026557922},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.11859935522079468},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10188886523246765}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7436773180961609},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6934003829956055},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6610627174377441},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6557894945144653},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5815070867538452},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.537472665309906},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.4782927632331848},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.46513834595680237},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4447614252567291},{"id":"https://openalex.org/C110593043","wikidata":"https://www.wikidata.org/wiki/Q7300787","display_name":"Real-time data","level":2,"score":0.4420422613620758},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.4289504289627075},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.4211128354072571},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4201250970363617},{"id":"https://openalex.org/C2781252014","wikidata":"https://www.wikidata.org/wiki/Q1141900","display_name":"Unstructured data","level":3,"score":0.4120887815952301},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40141531825065613},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39779698848724365},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3856322169303894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34874868392944336},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.22108468413352966},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.12261819839477539},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.11937502026557922},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.11859935522079468},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10188886523246765},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/itsc.2018.8569015","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2018.8569015","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 21st International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/1d9ec94c-757a-46be-b3cb-dcad276ac455","is_oa":false,"landing_page_url":"https://orbit.dtu.dk/en/publications/1d9ec94c-757a-46be-b3cb-dcad276ac455","pdf_url":null,"source":{"id":"https://openalex.org/S4306400705","display_name":"Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I96673099","host_organization_name":"Technical University of Denmark","host_organization_lineage":["https://openalex.org/I96673099"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Markou , I , Rodrigues , F &amp; Pereira , F C 2018 , Real-Time Taxi Demand Prediction using data from the web . in 2018 21st International Conference on Intelligent Transportation Systems (ITSC) . IEEE , pp. 1664-1671 , 21st International IEEE Conference on Intelligent Transportation Systems , Maui , Hawaii , United States , 04/11/2018 . https://doi.org/10.1109/ITSC.2018.8569015","raw_type":"contributionToPeriodical"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W197341177","https://openalex.org/W615344948","https://openalex.org/W1481376060","https://openalex.org/W1880262756","https://openalex.org/W1970598633","https://openalex.org/W1973803644","https://openalex.org/W1988580225","https://openalex.org/W1994377164","https://openalex.org/W2005236385","https://openalex.org/W2054296758","https://openalex.org/W2080678433","https://openalex.org/W2101234009","https://openalex.org/W2115737340","https://openalex.org/W2124499489","https://openalex.org/W2132968912","https://openalex.org/W2137958601","https://openalex.org/W2294749418","https://openalex.org/W2529205007","https://openalex.org/W2557606700","https://openalex.org/W2565638783","https://openalex.org/W2584174354","https://openalex.org/W2743316574","https://openalex.org/W2753977519","https://openalex.org/W2766311542","https://openalex.org/W2997591727","https://openalex.org/W4231510805","https://openalex.org/W4237747303","https://openalex.org/W6607940070","https://openalex.org/W6639619044","https://openalex.org/W6675354045","https://openalex.org/W6680441624","https://openalex.org/W6697091597","https://openalex.org/W6729567539","https://openalex.org/W6745348148","https://openalex.org/W6819203822"],"related_works":["https://openalex.org/W2990081132","https://openalex.org/W4296984035","https://openalex.org/W3108206468","https://openalex.org/W3127121676","https://openalex.org/W3091433184","https://openalex.org/W4245534163","https://openalex.org/W4289242525","https://openalex.org/W4386780631","https://openalex.org/W4401154840","https://openalex.org/W4386204182"],"abstract_inverted_index":{"In":[0,100],"transportation,":[1],"nature,":[2],"economy,":[3],"environment,":[4],"and":[5,21,40,70,107,182],"many":[6],"other":[7],"settings,":[8],"there":[9],"are":[10,16,153],"multiple":[11],"simultaneous":[12],"phenomena":[13],"happening":[14],"that":[15,31,65,82,123,149],"of":[17,47,89,118,133,169],"interest":[18],"to":[19,67,96,126,155],"model":[20,122],"predict.":[22],"Over":[23],"the":[24,28,45,87,116,134,150,158,161],"last":[25],"few":[26],"years,":[27],"traffic":[29,54],"data":[30,49,91,106,142],"we":[32,41,103,146,186],"have":[33,37,42],"at":[34],"our":[35,170],"disposal":[36],"significantly":[38,156],"increased,":[39],"truly":[43],"entered":[44],"era":[46],"big":[48],"for":[50,176],"transportation.":[51],"Most":[52],"existing":[53],"flow":[55],"prediction":[56,121],"methods":[57],"mainly":[58],"focus":[59,187],"on":[60,71,189],"capturing":[61],"recurrent":[62],"mobility":[63],"trends":[64],"relate":[66],"habitual/routine":[68],"behaviour,":[69],"exploiting":[72],"short-term":[73],"correlations":[74],"with":[75],"recent":[76],"observation":[77],"patterns.":[78],"However,":[79],"valuable":[80],"information":[81,109],"is":[83,92,124,172],"often":[84],"available":[85,140],"in":[86,115,128,160],"form":[88],"unstructured":[90],"neglected":[93],"when":[94],"attempting":[95],"improve":[97],"forecasting":[98],"results.":[99],"this":[101],"paper,":[102],"explore":[104],"time-series":[105],"textual":[108],"combinations":[110],"using":[111],"machine":[112],"learning":[113],"techniques":[114],"context":[117],"creating":[119],"a":[120,177],"able":[125,154],"capture":[127],"real-time":[129],"future":[130],"stressful":[131],"situations":[132],"studied":[135],"transportation":[136],"system.":[137],"Using":[138],"publicly":[139],"taxi":[141],"from":[143],"New":[144],"York,":[145],"empirically":[147],"show":[148],"proposed":[151],"models":[152],"reduce":[157],"error":[159,167],"forecasts.":[162],"The":[163],"final":[164],"mean":[165],"absolute":[166],"(MAE)":[168],"predictions":[171],"decreased":[173],"by":[174,183],"19.5%":[175],"three":[178],"months":[179],"testing":[180],"period":[181],"57%":[184],"if":[185],"only":[188],"event":[190],"periods.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
