{"id":"https://openalex.org/W4417283655","doi":"https://doi.org/10.1145/3748636.3766527","title":"A Deep Origin-Destination Flow Imputation Model Informed by the Visitation Law in Human Mobility","display_name":"A Deep Origin-Destination Flow Imputation Model Informed by the Visitation Law in Human Mobility","publication_year":2025,"publication_date":"2025-11-03","ids":{"openalex":"https://openalex.org/W4417283655","doi":"https://doi.org/10.1145/3748636.3766527"},"language":null,"primary_location":{"id":"doi:10.1145/3748636.3766527","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3748636.3766527","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems","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/A5104102977","display_name":"Sheng Wang","orcid":"https://orcid.org/0009-0002-2573-2366"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]},{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sheng Wang","raw_affiliation_strings":["Department of Geography, Environment &amp; Society, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA"],"raw_orcid":"https://orcid.org/0009-0002-2573-2366","affiliations":[{"raw_affiliation_string":"Department of Geography, Environment &amp; Society, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA","institution_ids":["https://openalex.org/I2800403580","https://openalex.org/I4210101327","https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020452677","display_name":"Di Zhu","orcid":"https://orcid.org/0000-0002-3237-6032"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]},{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Di Zhu","raw_affiliation_strings":["Department of Geography, Environment &amp; Society, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA"],"raw_orcid":"https://orcid.org/0000-0002-3237-6032","affiliations":[{"raw_affiliation_string":"Department of Geography, Environment &amp; Society, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA","institution_ids":["https://openalex.org/I2800403580","https://openalex.org/I4210101327","https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5104102977"],"corresponding_institution_ids":["https://openalex.org/I130238516","https://openalex.org/I2800403580","https://openalex.org/I4210101327"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37544669,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1266","last_page":"1269"},"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":0.946399986743927,"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":0.946399986743927,"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/T11896","display_name":"Opportunistic and Delay-Tolerant Networks","score":0.009600000455975533,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11942","display_name":"Transportation and Mobility Innovations","score":0.008200000040233135,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/destinations","display_name":"Destinations","score":0.478300005197525},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.4666000008583069},{"id":"https://openalex.org/keywords/flow-network","display_name":"Flow network","score":0.4140999913215637},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4072999954223633},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.39730000495910645},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.3926999866962433},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.3869999945163727},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.3562999963760376}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5307999849319458},{"id":"https://openalex.org/C2776687071","wikidata":"https://www.wikidata.org/wiki/Q5265193","display_name":"Destinations","level":3,"score":0.478300005197525},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.4666000008583069},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.4140999913215637},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4072999954223633},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.39730000495910645},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.3926999866962433},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3869999945163727},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.3562999963760376},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.33180001378059387},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.3212999999523163},{"id":"https://openalex.org/C185767445","wikidata":"https://www.wikidata.org/wiki/Q207952","display_name":"Law of large numbers","level":3,"score":0.31709998846054077},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3133000135421753},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.3075999915599823},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30329999327659607},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.3018999993801117},{"id":"https://openalex.org/C54525549","wikidata":"https://www.wikidata.org/wiki/Q2553445","display_name":"Weaving","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.2759999930858612},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2736999988555908},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2711000144481659},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C2985733770","wikidata":"https://www.wikidata.org/wiki/Q1233007","display_name":"Travel time","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C3019814787","wikidata":"https://www.wikidata.org/wiki/Q17072952","display_name":"Free flow","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2524999976158142},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3748636.3766527","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3748636.3766527","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W630650518","https://openalex.org/W2760942449","https://openalex.org/W3039638631","https://openalex.org/W3040304705","https://openalex.org/W4404481987","https://openalex.org/W4411918669","https://openalex.org/W4412693363"],"related_works":[],"abstract_inverted_index":{"Collective":[0],"origin-destination":[1],"(OD)":[2],"flows":[3,48,149],"refer":[4],"to":[5,15,131],"the":[6,21,33,43,116],"total":[7],"number":[8],"of":[9,46],"visits":[10],"or":[11,83],"visitors":[12],"from":[13],"origins":[14],"destinations":[16],"within":[17],"a":[18,38,109,120,151],"region,":[19],"providing":[20],"basic":[22],"information":[23],"for":[24,41],"transportation":[25],"planning,":[26],"mobility":[27,140],"demand,":[28],"and":[29,63,77,100,123],"so":[30],"on.":[31],"Recently,":[32],"universal":[34],"visitation":[35,117],"law":[36,118],"provides":[37],"theoretical":[39],"foundation":[40],"understanding":[42],"statistical":[44],"structure":[45],"OD":[47,133,148],"by":[49,102],"modeling":[50],"their":[51],"underlying":[52],"visit":[53],"density":[54],"as":[55,73,119],"an":[56],"inverse-square":[57],"function":[58],"weaving":[59],"distance,":[60],"visiting":[61],"frequency,":[62],"attractiveness.":[64],"However,":[65],"its":[66,89],"closed-form":[67],"assumes":[68],"that":[69,114,143],"key":[70],"quantities,":[71],"such":[72,94],"attractiveness,":[74],"travel":[75],"friction,":[76],"frequency":[78],"spectrum,":[79],"are":[80,96],"externally":[81],"known":[82],"can":[84],"be":[85],"easily":[86],"estimated,":[87],"limiting":[88],"applicability":[90],"in":[91,150],"real-world,":[92],"where":[93],"factors":[95],"often":[97],"latent,":[98],"interdependent,":[99],"governed":[101],"nonlinearities.":[103],"In":[104],"this":[105],"work,":[106],"we":[107],"propose":[108],"deep":[110],"graph":[111],"learning":[112],"approach":[113],"incorporates":[115],"structural":[121],"prior":[122],"applies":[124],"additional":[125],"physical":[126],"constraints":[127],"on":[128,138],"neural":[129],"networks":[130],"guide":[132],"flow":[134],"imputation.":[135],"Experiments":[136],"based":[137],"real":[139],"data":[141],"show":[142],"our":[144],"method":[145],"effectively":[146],"imputes":[147],"data-driven":[152],"yet":[153],"theory-informed":[154],"manner.":[155]},"counts_by_year":[],"updated_date":"2025-12-13T23:11:00.310470","created_date":"2025-12-12T00:00:00"}
