{"id":"https://openalex.org/W3121125901","doi":"https://doi.org/10.1145/3416914","title":"Transfer Urban Human Mobility via POI Embedding over Multiple Cities","display_name":"Transfer Urban Human Mobility via POI Embedding over Multiple Cities","publication_year":2021,"publication_date":"2021-01-03","ids":{"openalex":"https://openalex.org/W3121125901","doi":"https://doi.org/10.1145/3416914","mag":"3121125901"},"language":"en","primary_location":{"id":"doi:10.1145/3416914","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3416914","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3416914","source":{"id":"https://openalex.org/S4210185969","display_name":"ACM/IMS Transactions on Data Science","issn_l":"2577-3224","issn":["2577-3224","2691-1922"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM/IMS Transactions on Data Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3416914","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040449880","display_name":"Renhe Jiang","orcid":"https://orcid.org/0000-0003-2593-4638"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Renhe Jiang","raw_affiliation_strings":["The University of Tokyo, Kashiwa, Japan"],"raw_orcid":"https://orcid.org/0000-0003-2593-4638","affiliations":[{"raw_affiliation_string":"The University of Tokyo, Kashiwa, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046856721","display_name":"Xuan Song","orcid":"https://orcid.org/0000-0003-4042-7888"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Song","raw_affiliation_strings":["SUSTech-UTokyo Joint Research Center on Super Smart City, Southern University of Science and Technology, The University of Tokyo, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SUSTech-UTokyo Joint Research Center on Super Smart City, Southern University of Science and Technology, The University of Tokyo, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009062546","display_name":"Zipei Fan","orcid":"https://orcid.org/0000-0002-1442-1530"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zipei Fan","raw_affiliation_strings":["SUSTech-UTokyo Joint Research Center on Super Smart City, Southern University of Science and Technology, The University of Tokyo, Kashiwa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SUSTech-UTokyo Joint Research Center on Super Smart City, Southern University of Science and Technology, The University of Tokyo, Kashiwa, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018819738","display_name":"Tianqi Xia","orcid":"https://orcid.org/0000-0003-4575-6883"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tianqi Xia","raw_affiliation_strings":["The University of Tokyo, Kashiwa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo, Kashiwa, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070106281","display_name":"Zhaonan Wang","orcid":"https://orcid.org/0000-0002-2613-9727"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zhaonan Wang","raw_affiliation_strings":["The University of Tokyo, Kashiwa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo, Kashiwa, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074092636","display_name":"Quanjun Chen","orcid":"https://orcid.org/0000-0001-6528-2924"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Quanjun Chen","raw_affiliation_strings":["SUSTech-UTokyo Joint Research Center on Super Smart City, Southern University of Science and Technology, The University of Tokyo, Kashiwa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SUSTech-UTokyo Joint Research Center on Super Smart City, Southern University of Science and Technology, The University of Tokyo, Kashiwa, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108659841","display_name":"Zekun Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zekun Cai","raw_affiliation_strings":["The University of Tokyo, Kashiwa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo, Kashiwa, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5105206953","display_name":"Ryosuke Shibasaki","orcid":"https://orcid.org/0000-0001-8760-244X"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryosuke Shibasaki","raw_affiliation_strings":["The University of Tokyo, Kashiwa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo, Kashiwa, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.0895,"has_fulltext":true,"cited_by_count":42,"citation_normalized_percentile":{"value":0.97740716,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"2","issue":"1","first_page":"1","last_page":"26"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9998000264167786,"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":0.9973000288009644,"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/T10298","display_name":"Urban Transport and Accessibility","score":0.9926000237464905,"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":0.7248640060424805},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4743543863296509},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46029385924339294},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.44003307819366455},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.4168376922607422},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3606678247451782},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2729995846748352}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7248640060424805},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4743543863296509},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46029385924339294},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.44003307819366455},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.4168376922607422},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3606678247451782},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2729995846748352},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3416914","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3416914","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3416914","source":{"id":"https://openalex.org/S4210185969","display_name":"ACM/IMS Transactions on Data Science","issn_l":"2577-3224","issn":["2577-3224","2691-1922"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM/IMS Transactions on Data Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3416914","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3416914","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3416914","source":{"id":"https://openalex.org/S4210185969","display_name":"ACM/IMS Transactions on Data Science","issn_l":"2577-3224","issn":["2577-3224","2691-1922"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM/IMS Transactions on Data Science","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.8199999928474426}],"awards":[{"id":"https://openalex.org/G4984633598","display_name":"A Benchmark for Video-Like Urban Computing on Citywide Crowd and Traffic Prediction","funder_award_id":"20K19859","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G7531168543","display_name":"An Online Adaptive Boosting Ensemble Approach to Human Mobility Prediction at a Metropolitan Scale","funder_award_id":"20K19782","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8546358048","display_name":"Fusion of sensing and simulation of tsunami damage assessment towards innovation of disaster medical system","funder_award_id":"17H06108","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3121125901.pdf","grobid_xml":"https://content.openalex.org/works/W3121125901.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W273955616","https://openalex.org/W1924770834","https://openalex.org/W1947481528","https://openalex.org/W1972436494","https://openalex.org/W1976094288","https://openalex.org/W2004353783","https://openalex.org/W2009779426","https://openalex.org/W2036785686","https://openalex.org/W2062017159","https://openalex.org/W2062231365","https://openalex.org/W2064675550","https://openalex.org/W2074020083","https://openalex.org/W2112738128","https://openalex.org/W2112796928","https://openalex.org/W2122111042","https://openalex.org/W2128420091","https://openalex.org/W2132504805","https://openalex.org/W2153207204","https://openalex.org/W2165698076","https://openalex.org/W2165991108","https://openalex.org/W2172211955","https://openalex.org/W2424778531","https://openalex.org/W2534727297","https://openalex.org/W2576554443","https://openalex.org/W2759083144","https://openalex.org/W2771472444","https://openalex.org/W2782298158","https://openalex.org/W2791723757","https://openalex.org/W2794492456","https://openalex.org/W2990138404","https://openalex.org/W4213069590","https://openalex.org/W4249402564","https://openalex.org/W6610017368"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347","https://openalex.org/W4210805261"],"abstract_inverted_index":{"Rapidly":[0],"developing":[1],"location":[2],"acquisition":[3],"technologies":[4,121],"provide":[5],"a":[6,46,69,132,158,166,172,218,244],"powerful":[7],"tool":[8],"for":[9,21,62,148,221],"understanding":[10],"and":[11,26,54,105,152,186,263],"predicting":[12],"human":[13,77,95,102,236],"mobility":[14,44,103,200,237],"in":[15,45,79,161],"cities,":[16],"which":[17,88,252],"is":[18,35,196],"very":[19],"significant":[20],"urban":[22,48,150,258],"planning,":[23],"traffic":[24],"regulation,":[25],"emergency":[27],"management.":[28],"However,":[29],"with":[30,84,114,178,225],"the":[31,73,91,111,138,184,190,222,240],"existing":[32],"methodologies,":[33],"it":[34],"still":[36],"difficult":[37],"to":[38,68,100,109,143,157,165,180,198,205,216],"accurately":[39],"predict":[40],"millions":[41],"of":[42,72,94,235,247,260],"peoples\u2019":[43],"large":[47],"area":[49],"such":[50],"as":[51,249],"Tokyo,":[52],"Shanghai,":[53],"Hong":[55],"Kong,":[56],"especially":[57],"when":[58],"collected":[59],"data":[60,104,108,215,228],"used":[61],"model":[63,220],"training":[64,116,250],"are":[65,81],"often":[66],"limited":[67,115,227,245],"small":[70],"portion":[71],"total":[74],"population.":[75],"Obviously,":[76],"activities":[78],"city":[80,106,204,224],"closely":[82],"linked":[83],"point-of-interest":[85],"(POI)":[86],"information,":[87],"can":[89,122,210],"reflect":[90],"semantic":[92],"meaning":[93],"mobility.":[96],"This":[97],"motivates":[98],"us":[99],"fuse":[101],"POI":[107],"improve":[110],"prediction":[112,238],"performance":[113,234],"data,":[117,251],"but":[118],"current":[119],"fusion":[120],"hardly":[123],"handle":[124],"these":[125],"two":[126],"heterogeneous":[127],"data.":[128],"Therefore,":[129],"we":[130,170,209,231],"propose":[131],"unique":[133],"POI-embedding":[134],"mechanism,":[135],"that":[136,208],"aggregates":[137],"regional":[139],"POIs":[140],"by":[141],"categories":[142],"generate":[144],"an":[145,162],"artificial":[146],"POI-image":[147],"each":[149,154],"grid":[151],"enriches":[153],"trajectory":[155],"snippet":[156],"four-dimensional":[159],"tensor":[160],"analogous":[163],"manner":[164],"short":[167],"video.":[168],"Then,":[169],"design":[171],"deep":[173],"learning":[174,195],"architecture":[175],"combining":[176],"CNN":[177],"LSTM":[179],"simultaneously":[181],"capture":[182],"both":[183],"spatiotemporal":[185],"geographical":[187],"information":[188],"from":[189,202],"enriched":[191],"trajectories.":[192],"Furthermore,":[193],"transfer":[194,199],"employed":[197],"knowledge":[201],"one":[203],"another,":[206],"so":[207],"fully":[211],"utilize":[212],"other":[213],"cities\u2019":[214],"train":[217],"stronger":[219],"target":[223],"only":[226],"available.":[229],"Finally,":[230],"achieve":[232],"satisfactory":[233],"at":[239],"citywide":[241],"level":[242],"using":[243],"amount":[246],"trajectories":[248],"has":[253],"been":[254],"validated":[255],"over":[256],"five":[257],"areas":[259],"different":[261],"types":[262],"scales.":[264]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-09T07:52:08.696243","created_date":"2025-10-10T00:00:00"}
