{"id":"https://openalex.org/W4390100363","doi":"https://doi.org/10.1145/3589132.3625651","title":"One Model Fits All: Cross-Region Taxi-Demand Forecasting","display_name":"One Model Fits All: Cross-Region Taxi-Demand Forecasting","publication_year":2023,"publication_date":"2023-11-13","ids":{"openalex":"https://openalex.org/W4390100363","doi":"https://doi.org/10.1145/3589132.3625651"},"language":"en","primary_location":{"id":"doi:10.1145/3589132.3625651","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589132.3625651","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3625651","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3625651","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011872712","display_name":"Ren Ozeki","orcid":"https://orcid.org/0000-0003-4237-4644"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Ren Ozeki","raw_affiliation_strings":["Osaka University, Suita, Japan"],"raw_orcid":"https://orcid.org/0000-0003-4237-4644","affiliations":[{"raw_affiliation_string":"Osaka University, Suita, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023279673","display_name":"Haruki Yonekura","orcid":"https://orcid.org/0000-0001-8184-3883"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Haruki Yonekura","raw_affiliation_strings":["Osaka University, Suita, Japan"],"raw_orcid":"https://orcid.org/0000-0001-8184-3883","affiliations":[{"raw_affiliation_string":"Osaka University, Suita, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039437696","display_name":"Aidana Baimbetova","orcid":"https://orcid.org/0009-0001-8448-1889"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Aidana Baimbetova","raw_affiliation_strings":["Osaka University, Suita, Japan"],"raw_orcid":"https://orcid.org/0009-0001-8448-1889","affiliations":[{"raw_affiliation_string":"Osaka University, Suita, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013317917","display_name":"Hamada Rizk","orcid":"https://orcid.org/0000-0002-8278-8801"},"institutions":[{"id":"https://openalex.org/I21376657","display_name":"Tanta University","ror":"https://ror.org/016jp5b92","country_code":"EG","type":"education","lineage":["https://openalex.org/I21376657"]},{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["EG","JP"],"is_corresponding":false,"raw_author_name":"Hamada Rizk","raw_affiliation_strings":["Osaka University, Suita, Japan","Tanta University, Tanta, Egypt","Osaka University, Suita, Japan Tanta University, Tanta, Egypt"],"raw_orcid":"https://orcid.org/0000-0002-8278-8801","affiliations":[{"raw_affiliation_string":"Osaka University, Suita, Japan","institution_ids":["https://openalex.org/I98285908"]},{"raw_affiliation_string":"Tanta University, Tanta, Egypt","institution_ids":["https://openalex.org/I21376657"]},{"raw_affiliation_string":"Osaka University, Suita, Japan Tanta University, Tanta, Egypt","institution_ids":["https://openalex.org/I21376657","https://openalex.org/I98285908"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084448172","display_name":"Hirozumi Yamaguchi","orcid":"https://orcid.org/0000-0003-2273-4876"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hirozumi Yamaguchi","raw_affiliation_strings":["Osaka University, Suita, Japan"],"raw_orcid":"https://orcid.org/0000-0003-2273-4876","affiliations":[{"raw_affiliation_string":"Osaka University, Suita, Japan","institution_ids":["https://openalex.org/I98285908"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5011872712"],"corresponding_institution_ids":["https://openalex.org/I98285908"],"apc_list":null,"apc_paid":null,"fwci":0.6514,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.6865162,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"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/T11942","display_name":"Transportation and Mobility Innovations","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"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":0.9993000030517578,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9983000159263611,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7166552543640137},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6688621044158936},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.6439061164855957},{"id":"https://openalex.org/keywords/demand-forecasting","display_name":"Demand forecasting","score":0.4875008761882782},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4514521360397339},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4492243826389313},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.4177376627922058},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3672071397304535},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.255206823348999},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.2432851791381836},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09577342867851257},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07177361845970154}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7166552543640137},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6688621044158936},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.6439061164855957},{"id":"https://openalex.org/C193809577","wikidata":"https://www.wikidata.org/wiki/Q3409300","display_name":"Demand forecasting","level":2,"score":0.4875008761882782},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4514521360397339},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4492243826389313},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.4177376627922058},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3672071397304535},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.255206823348999},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.2432851791381836},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09577342867851257},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07177361845970154},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589132.3625651","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589132.3625651","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3625651","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3589132.3625651","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589132.3625651","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3625651","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7300000190734863,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G6718509927","display_name":null,"funder_award_id":"CREST","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G7116398426","display_name":null,"funder_award_id":"22K12011","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8159118636","display_name":null,"funder_award_id":"JPMJCR21M5","funder_id":"https://openalex.org/F4320338075","funder_display_name":"Core Research for Evolutional Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320338075","display_name":"Core Research for Evolutional Science and Technology","ror":"https://ror.org/00097mb19"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390100363.pdf","grobid_xml":"https://content.openalex.org/works/W4390100363.grobid-xml"},"referenced_works_count":7,"referenced_works":["https://openalex.org/W1969454839","https://openalex.org/W2290888990","https://openalex.org/W2766311542","https://openalex.org/W2962756421","https://openalex.org/W2962960549","https://openalex.org/W2964275023","https://openalex.org/W3008392016"],"related_works":["https://openalex.org/W2118717649","https://openalex.org/W2413243053","https://openalex.org/W410723623","https://openalex.org/W2015341305","https://openalex.org/W2035068594","https://openalex.org/W4225593417","https://openalex.org/W2573498121","https://openalex.org/W3022298670","https://openalex.org/W3160494304","https://openalex.org/W2891286602"],"abstract_inverted_index":{"The":[0,98],"growing":[1],"demand":[2,15,35,104],"for":[3,12,139],"ride-hailing":[4],"services":[5,142],"has":[6],"led":[7],"to":[8,21,26,44,63,71,88,109],"an":[9],"increasing":[10],"need":[11],"accurate":[13],"taxi":[14,34,103,128,141],"prediction.":[16],"Existing":[17],"systems":[18],"are":[19],"limited":[20],"specific":[22],"regions,":[23,134],"lacking":[24],"generalizability":[25],"unseen":[27,75],"areas.":[28,115],"This":[29],"paper":[30],"presents":[31],"a":[32,40,58,65,148],"novel":[33],"forecasting":[36,127],"system":[37,56,124],"that":[38,67],"leverages":[39],"graph":[41],"neural":[42],"network":[43],"capture":[45],"spatial":[46],"dependencies":[47],"and":[48,95,143],"patterns":[49],"in":[50,125,131],"urban":[51,114],"environments.":[52],"Additionally,":[53],"the":[54,80,83,90,107,119,122],"proposed":[55,123],"employs":[57],"region-neutral":[59,96,99],"approach,":[60],"enabling":[61],"it":[62],"train":[64],"model":[66,108],"can":[68],"be":[69],"applied":[70],"any":[72],"region,":[73],"including":[74],"regions.":[76],"To":[77],"achieve":[78],"this,":[79],"framework":[81],"incorporates":[82],"power":[84],"of":[85,121],"Variational":[86],"Autoencoder":[87],"disentangle":[89],"input":[91],"features":[92,100],"into":[93],"region-specific":[94],"components.":[97],"facilitate":[101],"cross-region":[102],"predictions,":[105],"allowing":[106],"generalize":[110],"well":[111],"across":[112],"different":[113],"Experimental":[116],"results":[117],"demonstrate":[118],"effectiveness":[120],"accurately":[126],"demand,":[129],"even":[130],"previously":[132],"unobserved":[133],"thus":[135],"showcasing":[136],"its":[137],"potential":[138],"optimizing":[140],"improving":[144],"transportation":[145],"efficiency":[146],"on":[147],"broader":[149],"scale.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}