{"id":"https://openalex.org/W3015302520","doi":"https://doi.org/10.1109/tkde.2020.2985954","title":"Incorporating Multi-Source Urban Data for Personalized and Context-Aware Multi-Modal Transportation Recommendation","display_name":"Incorporating Multi-Source Urban Data for Personalized and Context-Aware Multi-Modal Transportation Recommendation","publication_year":2020,"publication_date":"2020-04-10","ids":{"openalex":"https://openalex.org/W3015302520","doi":"https://doi.org/10.1109/tkde.2020.2985954","mag":"3015302520"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2020.2985954","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2020.2985954","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","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/A5100458897","display_name":"Hao Liu","orcid":"https://orcid.org/0000-0003-4271-1567"},"institutions":[{"id":"https://openalex.org/I4210129579","display_name":"National Engineering Laboratory of Deep Learning Technology and Application","ror":"https://ror.org/03z8p5796","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210129579"]},{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Liu","raw_affiliation_strings":["Business Intelligence Lab, Baidu Research, National Engineering Laboratory of Deep Learning Technology and Application, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4271-1567","affiliations":[{"raw_affiliation_string":"Business Intelligence Lab, Baidu Research, National Engineering Laboratory of Deep Learning Technology and Application, Beijing, China","institution_ids":["https://openalex.org/I4210129579","https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051874566","display_name":"Yongxin Tong","orcid":"https://orcid.org/0000-0002-5598-0312"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongxin Tong","raw_affiliation_strings":["SKLSDE Lab, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5598-0312","affiliations":[{"raw_affiliation_string":"SKLSDE Lab, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102879609","display_name":"Jindong Han","orcid":"https://orcid.org/0000-0001-6329-7524"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jindong Han","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6329-7524","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100411733","display_name":"Panpan Zhang","orcid":"https://orcid.org/0000-0002-8211-5930"},"institutions":[{"id":"https://openalex.org/I4210129579","display_name":"National Engineering Laboratory of Deep Learning Technology and Application","ror":"https://ror.org/03z8p5796","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210129579"]},{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Panpan Zhang","raw_affiliation_strings":["Business Intelligence Lab, Baidu Research, National Engineering Laboratory of Deep Learning Technology and Application, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Business Intelligence Lab, Baidu Research, National Engineering Laboratory of Deep Learning Technology and Application, Beijing, China","institution_ids":["https://openalex.org/I4210129579","https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047229109","display_name":"Xinjiang Lu","orcid":"https://orcid.org/0000-0002-3602-0391"},"institutions":[{"id":"https://openalex.org/I4210129579","display_name":"National Engineering Laboratory of Deep Learning Technology and Application","ror":"https://ror.org/03z8p5796","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210129579"]},{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinjiang Lu","raw_affiliation_strings":["Business Intelligence Lab, Baidu Research, National Engineering Laboratory of Deep Learning Technology and Application, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3602-0391","affiliations":[{"raw_affiliation_string":"Business Intelligence Lab, Baidu Research, National Engineering Laboratory of Deep Learning Technology and Application, Beijing, China","institution_ids":["https://openalex.org/I4210129579","https://openalex.org/I98301712"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101862104","display_name":"Hui Xiong","orcid":"https://orcid.org/0000-0001-6016-6465"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hui Xiong","raw_affiliation_strings":["Management Science and Information Systems Department, Rutgers University, Newark, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Management Science and Information Systems Department, Rutgers University, Newark, USA","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.2101,"has_fulltext":false,"cited_by_count":75,"citation_normalized_percentile":{"value":0.96310002,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"34","issue":"2","first_page":"723","last_page":"735"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9994999766349792,"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"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9980000257492065,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/computer-science","display_name":"Computer science","score":0.7294166684150696},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.6538721323013306},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.49668580293655396},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.47145944833755493},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13617092370986938},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10101443529129028}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7294166684150696},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.6538721323013306},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.49668580293655396},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.47145944833755493},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13617092370986938},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10101443529129028},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2020.2985954","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2020.2985954","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W98895690","https://openalex.org/W1522301498","https://openalex.org/W1936915774","https://openalex.org/W2017694061","https://openalex.org/W2024046085","https://openalex.org/W2025267865","https://openalex.org/W2031674781","https://openalex.org/W2037403365","https://openalex.org/W2066625239","https://openalex.org/W2070493638","https://openalex.org/W2097484305","https://openalex.org/W2115584760","https://openalex.org/W2126194848","https://openalex.org/W2146950091","https://openalex.org/W2148831787","https://openalex.org/W2150370140","https://openalex.org/W2154851992","https://openalex.org/W2163812848","https://openalex.org/W2263919949","https://openalex.org/W2295598076","https://openalex.org/W2475334473","https://openalex.org/W2482213519","https://openalex.org/W2604662567","https://openalex.org/W2735758519","https://openalex.org/W2743316574","https://openalex.org/W2753709519","https://openalex.org/W2794024860","https://openalex.org/W2798728990","https://openalex.org/W2809159945","https://openalex.org/W2889125237","https://openalex.org/W2904403013","https://openalex.org/W2908972570","https://openalex.org/W2953071387","https://openalex.org/W2962756421","https://openalex.org/W3104097132","https://openalex.org/W6604031572","https://openalex.org/W6631190155","https://openalex.org/W6654186649","https://openalex.org/W6677385034","https://openalex.org/W6682118432","https://openalex.org/W6682691769","https://openalex.org/W6684773713","https://openalex.org/W6913010783"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2963177394","https://openalex.org/W2024638892","https://openalex.org/W763418848","https://openalex.org/W1595229445","https://openalex.org/W1965815883","https://openalex.org/W149041114","https://openalex.org/W4313359513","https://openalex.org/W322408318"],"abstract_inverted_index":{"Transportation":[0],"recommendation":[1,12,51,177,189,240],"is":[2,59],"one":[3,27],"important":[4],"map":[5,213],"service":[6],"in":[7,26,230],"navigation":[8],"applications.":[9],"Previous":[10],"transportation":[11,28,56,108,132,143,166],"solutions":[13],"fail":[14],"to":[15,61,112,156,196],"deliver":[16],"satisfactory":[17],"user":[18,136,265],"experience":[19],"because":[20],"their":[21],"recommendations":[22],"only":[23],"consider":[24],"routes":[25,98],"mode":[29,144],"(uni-modal,":[30],"e.g.,":[31],"taxi,":[32],"bus,":[33],"cycle)":[34],"and":[35,58,70,80,84,93,131,148,164,179,184,202,221,253,259],"largely":[36],"overlook":[37],"situational":[38,63],"context.":[39],"In":[40,110],"this":[41],"work,":[42],"we":[43,121,152],"propose$\\mathsf":[44],"{Hydra}$,":[45],"a":[46,86,169,181,236],"multi-task":[47,182],"deep":[48,185],"learning":[49,186],"based":[50,134,176,188,251,255],"system":[52],"that":[53,90],"offers":[54],"multi-modal":[55,94,107,165],"planning":[57],"adaptive":[60],"various":[62,162],"context":[64,114],"(e.g.,":[65,95],"nearby":[66],"point-of-interest":[67],"(POI)":[68],"distribution":[69],"weather).":[71],"We":[72,191,204],"leverage":[73],"the":[74,123,141,158,194,210,219],"availability":[75],"of":[76,126,146,209,223,264],"existing":[77],"routing":[78],"engines":[79],"big":[81],"urban":[82,103,113,119],"data,":[83,120],"design":[85],"novel":[87],"two-level":[88],"framework":[89,195],"integrates":[91],"uni-modal":[92,163],"taxi-bus,":[96],"bus-cycle)":[97],"as":[99,101],"well":[100],"heterogeneous":[102],"data":[104],"for":[105],"intelligent":[106],"recommendation.":[109,203],"addition":[111],"features":[115],"constructed":[116],"from":[117],"multi-source":[118],"learn":[122],"latent":[124],"representations":[125],"users,":[127],"origin-destination":[128],"(OD)":[129],"pairs":[130],"modes":[133],"on":[135],"implicit":[137],"feedbacks,":[138],"which":[139],"captures":[140],"collaborative":[142],"preferences":[145],"users":[147],"OD":[149],"pairs.":[150],"Moreover,":[151],"propose":[153],"two":[154],"models":[155],"recommend":[157],"proper":[159],"route":[160,200,239],"among":[161],"routes:":[167],"(1)":[168],"light-weight":[170],"gradient":[171],"boosting":[172],"decision":[173],"tree":[174],"(GBDT)":[175],"model;":[178],"(2)":[180],"wide":[183],"(MTWDL)":[187],"model.":[190],"also":[192],"optimize":[193],"support":[197],"real-time,":[198],"large-scale":[199],"query":[201],"deploy$\\mathsf":[205],"{Hydra}$on":[206],"Baidu":[207],"Maps,11.https://maps.baidu.com/.one":[208],"world's":[211],"largest":[212],"services.":[214],"Real-world":[215],"urban-scale":[216],"experiments":[217],"demonstrate":[218],"effectiveness":[220],"efficiency":[222],"our":[224],"proposed":[225],"system.":[226],"Since":[227],"its":[228],"deployment":[229],"August":[231],"2018,$\\mathsf":[232],"{Hydra}$has":[233],"answered":[234],"over":[235,244],"hundred":[237],"million":[238,246],"queries":[241],"made":[242],"by":[243],"ten":[245],"distinct":[247],"users.":[248],"The":[249],"GBDT":[250],"model":[252,256],"MTWDL":[254],"achieve":[257],"82.8":[258],"96.6":[260],"percent":[261],"relative":[262],"improvement":[263],"click":[266],"ratio,":[267],"respectively.":[268]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":22},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":4}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
