{"id":"https://openalex.org/W4405360404","doi":"https://doi.org/10.1109/tmc.2024.3517332","title":"Exploring Context Generalizability in Citywide Crowd Mobility Prediction: An Analytic Framework and Benchmark","display_name":"Exploring Context Generalizability in Citywide Crowd Mobility Prediction: An Analytic Framework and Benchmark","publication_year":2024,"publication_date":"2024-12-13","ids":{"openalex":"https://openalex.org/W4405360404","doi":"https://doi.org/10.1109/tmc.2024.3517332"},"language":"en","primary_location":{"id":"doi:10.1109/tmc.2024.3517332","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2024.3517332","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"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 Mobile Computing","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/A5048303070","display_name":"Liyue Chen","orcid":"https://orcid.org/0000-0002-8540-5589"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liyue Chen","raw_affiliation_strings":["Key Lab of High Confidence Software Technologies, Ministry of Education, School of Computer Science, Peking University, Beijing, China","Key Lab of High Confidence Software Technologies, Ministry of Education, China"],"raw_orcid":"https://orcid.org/0000-0002-8540-5589","affiliations":[{"raw_affiliation_string":"Key Lab of High Confidence Software Technologies, Ministry of Education, School of Computer Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Key Lab of High Confidence Software Technologies, Ministry of Education, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100679196","display_name":"Xiaoxiang Wang","orcid":"https://orcid.org/0000-0002-2924-2295"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoxiang Wang","raw_affiliation_strings":["School of Software and Microelectronics, Peking University, Beijing, China","School of Computer Science, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software and Microelectronics, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"School of Computer Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055087680","display_name":"Leye Wang","orcid":"https://orcid.org/0000-0002-7627-8485"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leye Wang","raw_affiliation_strings":["Key Lab of High Confidence Software Technologies, Ministry of Education, School of Computer Science, Peking University, Beijing, China","Key Lab of High Confidence Software Technologies, Ministry of Education, China"],"raw_orcid":"https://orcid.org/0000-0002-7627-8485","affiliations":[{"raw_affiliation_string":"Key Lab of High Confidence Software Technologies, Ministry of Education, School of Computer Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Key Lab of High Confidence Software Technologies, Ministry of Education, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":1.0991,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.82615268,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"24","issue":"5","first_page":"3597","last_page":"3614"},"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":0.9994000196456909,"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":0.9994000196456909,"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":0.9811000227928162,"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9750000238418579,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.7974869012832642},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7389629483222961},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7345868349075317},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6418436169624329},{"id":"https://openalex.org/keywords/crowd-sourcing","display_name":"Crowd sourcing","score":0.5021741390228271},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38637763261795044},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3761324882507324},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32516661286354065},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1941874921321869},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12216702103614807},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08374488353729248}],"concepts":[{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.7974869012832642},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7389629483222961},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7345868349075317},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6418436169624329},{"id":"https://openalex.org/C3018396927","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowd sourcing","level":2,"score":0.5021741390228271},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38637763261795044},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3761324882507324},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32516661286354065},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1941874921321869},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12216702103614807},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08374488353729248},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmc.2024.3517332","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2024.3517332","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"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 Mobile Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":111,"referenced_works":["https://openalex.org/W1892382968","https://openalex.org/W1990444226","https://openalex.org/W2005436527","https://openalex.org/W2064675550","https://openalex.org/W2125817951","https://openalex.org/W2295598076","https://openalex.org/W2297059404","https://openalex.org/W2460480794","https://openalex.org/W2463743813","https://openalex.org/W2514936170","https://openalex.org/W2519091744","https://openalex.org/W2528040708","https://openalex.org/W2528639018","https://openalex.org/W2530386080","https://openalex.org/W2561568083","https://openalex.org/W2614121823","https://openalex.org/W2695874637","https://openalex.org/W2743316574","https://openalex.org/W2751802138","https://openalex.org/W2752782242","https://openalex.org/W2756203131","https://openalex.org/W2782286280","https://openalex.org/W2783519195","https://openalex.org/W2788134583","https://openalex.org/W2808377988","https://openalex.org/W2808535700","https://openalex.org/W2809035759","https://openalex.org/W2884738862","https://openalex.org/W2903871660","https://openalex.org/W2904765547","https://openalex.org/W2904813135","https://openalex.org/W2904832339","https://openalex.org/W2910892140","https://openalex.org/W2911432088","https://openalex.org/W2912985636","https://openalex.org/W2921532413","https://openalex.org/W2950817888","https://openalex.org/W2952613166","https://openalex.org/W2952734551","https://openalex.org/W2962989616","https://openalex.org/W2963214893","https://openalex.org/W2965341826","https://openalex.org/W2966783050","https://openalex.org/W2968911474","https://openalex.org/W2969424631","https://openalex.org/W2983997240","https://openalex.org/W2996847713","https://openalex.org/W2997848713","https://openalex.org/W3005082831","https://openalex.org/W3008621121","https://openalex.org/W3033688252","https://openalex.org/W3034215963","https://openalex.org/W3034246913","https://openalex.org/W3037147042","https://openalex.org/W3038304141","https://openalex.org/W3038876156","https://openalex.org/W3048586323","https://openalex.org/W3080252065","https://openalex.org/W3082935815","https://openalex.org/W3088611441","https://openalex.org/W3091641260","https://openalex.org/W3120437934","https://openalex.org/W3156972038","https://openalex.org/W3157414468","https://openalex.org/W3158304688","https://openalex.org/W3161226789","https://openalex.org/W3168115244","https://openalex.org/W3170140111","https://openalex.org/W3171958173","https://openalex.org/W3173213819","https://openalex.org/W3174144901","https://openalex.org/W3177028972","https://openalex.org/W3177318507","https://openalex.org/W3207461654","https://openalex.org/W3214699261","https://openalex.org/W3215281442","https://openalex.org/W3217450528","https://openalex.org/W4210432862","https://openalex.org/W4213088607","https://openalex.org/W4224326696","https://openalex.org/W4224439980","https://openalex.org/W4225543494","https://openalex.org/W4234816175","https://openalex.org/W4285182450","https://openalex.org/W4289533915","https://openalex.org/W4290944300","https://openalex.org/W4290944372","https://openalex.org/W4301395451","https://openalex.org/W4319998098","https://openalex.org/W4381786018","https://openalex.org/W4384789416","https://openalex.org/W4386081284","https://openalex.org/W4386320464","https://openalex.org/W4392384923","https://openalex.org/W4399794065","https://openalex.org/W4400909948","https://openalex.org/W4401863290","https://openalex.org/W6628877408","https://openalex.org/W6636914306","https://openalex.org/W6640212811","https://openalex.org/W6679436768","https://openalex.org/W6726873649","https://openalex.org/W6731370813","https://openalex.org/W6746015598","https://openalex.org/W6748850308","https://openalex.org/W6773017188","https://openalex.org/W6780221082","https://openalex.org/W6797155008","https://openalex.org/W6802495884","https://openalex.org/W6810637551","https://openalex.org/W6846376059"],"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/W2388888344"],"abstract_inverted_index":{"Contextual":[0],"features":[1,26,102,148],"are":[2],"important":[3,96],"data":[4],"sources":[5],"for":[6,54,166,177],"building":[7,167],"citywide":[8],"crowd":[9,61,76,168],"mobility":[10,62,77,169],"prediction":[11,68,78,109,152,170],"models.":[12,69],"However,":[13],"the":[14,21,117,150],"difficulty":[15],"of":[16,24,32,119],"applying":[17],"context":[18,35,56,112,137,185],"lies":[19],"in":[20,74,107,115],"unknown":[22],"generalizability":[23],"contextual":[25,64,101,132,147,164],"(e.g.,":[27],"weather,":[28],"holiday,":[29],"and":[30,34,50,66,87,121],"points":[31],"interests)":[33],"modeling":[36,113,138,186],"techniques":[37],"across":[38],"different":[39],"scenarios.":[40],"In":[41,136],"this":[42],"paper,":[43],"we":[44,158,175],"present":[45],"a":[46,51,141],"unified":[47],"analytic":[48],"framework":[49],"large-scale":[52],"benchmark":[53,59],"evaluating":[55],"generalizability.":[57,156],"The":[58],"includes":[60],"data,":[63,65],"advanced":[67],"We":[70],"conduct":[71],"comprehensive":[72],"experiments":[73],"several":[75,95,160],"tasks":[79],"such":[80],"as":[81],"bike":[82],"flow,":[83,86],"metro":[84],"passenger":[85],"electric":[88],"vehicle":[89],"charging":[90],"demand.":[91],"Our":[92],"results":[93],"reveal":[94],"observations:":[97],"(1)":[98],"Using":[99],"more":[100,126],"may":[103],"not":[104],"always":[105],"result":[106],"better":[108],"with":[110],"existing":[111],"techniques;":[114],"particular,":[116],"combination":[118],"holiday":[120],"temporal":[122],"position":[123],"can":[124],"provide":[125],"generalizable":[127],"beneficial":[128],"information":[129],"than":[130],"other":[131],"feature":[133],"combinations.":[134],"(2)":[135],"techniques,":[139],"using":[140],"gated":[142],"unit":[143],"to":[144,182],"incorporate":[145],"raw":[146],"into":[149],"deep":[151],"model":[153],"has":[154],"good":[155],"Besides,":[157],"offer":[159],"suggestions":[161],"about":[162],"incorporating":[163],"factors":[165],"applications.":[171],"From":[172],"our":[173],"findings,":[174],"call":[176],"future":[178],"research":[179],"efforts":[180],"devoted":[181],"developing":[183],"new":[184],"solutions.":[187]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}