{"id":"https://openalex.org/W4417283681","doi":"https://doi.org/10.1145/3748636.3762775","title":"POIFormer: A Transformer-Based Framework for Accurate and Scalable Point-of-Interest Attribution","display_name":"POIFormer: A Transformer-Based Framework for Accurate and Scalable Point-of-Interest Attribution","publication_year":2025,"publication_date":"2025-11-03","ids":{"openalex":"https://openalex.org/W4417283681","doi":"https://doi.org/10.1145/3748636.3762775","pmid":"https://pubmed.ncbi.nlm.nih.gov/41972096"},"language":"en","primary_location":{"id":"doi:10.1145/3748636.3762775","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748636.3762775","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3748636.3762775","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":"conference-paper","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3748636.3762775","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091625866","display_name":"Nripsuta Ani Saxena","orcid":"https://orcid.org/0009-0004-1121-5426"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I2800817003","display_name":"California Southern University","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nripsuta Ani Saxena","raw_affiliation_strings":["University of Southern California, California, California, USA"],"raw_orcid":"https://orcid.org/0009-0004-1121-5426","affiliations":[{"raw_affiliation_string":"University of Southern California, California, California, USA","institution_ids":["https://openalex.org/I1174212","https://openalex.org/I2800817003"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035816658","display_name":"Shang-Ling Hsu","orcid":"https://orcid.org/0009-0005-1096-0405"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I2800817003","display_name":"California Southern University","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shang-Ling Hsu","raw_affiliation_strings":["University of Southern California, California, California, USA"],"raw_orcid":"https://orcid.org/0009-0005-1096-0405","affiliations":[{"raw_affiliation_string":"University of Southern California, California, California, USA","institution_ids":["https://openalex.org/I1174212","https://openalex.org/I2800817003"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110724688","display_name":"Martin Shetty","orcid":"https://orcid.org/0009-0000-0528-2471"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I2800817003","display_name":"California Southern University","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mehul Shetty","raw_affiliation_strings":["University of Southern California, California, California, USA"],"raw_orcid":"https://orcid.org/0009-0000-0528-2471","affiliations":[{"raw_affiliation_string":"University of Southern California, California, California, USA","institution_ids":["https://openalex.org/I1174212","https://openalex.org/I2800817003"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120787857","display_name":"Omar Alkhadra","orcid":"https://orcid.org/0009-0006-4402-4380"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I2800817003","display_name":"California Southern University","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Omar Alkhadra","raw_affiliation_strings":["University of Southern California, California, California, USA"],"raw_orcid":"https://orcid.org/0009-0006-4402-4380","affiliations":[{"raw_affiliation_string":"University of Southern California, California, California, USA","institution_ids":["https://openalex.org/I1174212","https://openalex.org/I2800817003"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012068017","display_name":"Cyrus Shahabi","orcid":"https://orcid.org/0000-0001-9118-0681"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I2800817003","display_name":"California Southern University","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cyrus Shahabi","raw_affiliation_strings":["University of Southern California, California, California, USA"],"raw_orcid":"https://orcid.org/0000-0001-9118-0681","affiliations":[{"raw_affiliation_string":"University of Southern California, California, California, USA","institution_ids":["https://openalex.org/I1174212","https://openalex.org/I2800817003"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113886631","display_name":"Abigail L. Horn","orcid":"https://orcid.org/0000-0002-5916-841X"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I2800817003","display_name":"California Southern University","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abigail L. Horn","raw_affiliation_strings":["University of Southern California, California, California, USA"],"raw_orcid":"https://orcid.org/0000-0002-5916-841X","affiliations":[{"raw_affiliation_string":"University of Southern California, California, California, USA","institution_ids":["https://openalex.org/I1174212","https://openalex.org/I2800817003"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2025","issue":null,"first_page":"607","last_page":"619"},"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":0.9783999919891357,"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":0.9783999919891357,"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/T11106","display_name":"Data Management and Algorithms","score":0.006200000178068876,"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/T11896","display_name":"Opportunistic and Delay-Tolerant Networks","score":0.004800000227987766,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/point-of-interest","display_name":"Point of interest","score":0.5591999888420105},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.48739999532699585},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44859999418258667},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.42669999599456787},{"id":"https://openalex.org/keywords/urban-computing","display_name":"Urban computing","score":0.4203000068664551},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.4032999873161316},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.3725999891757965},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.3357999920845032}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7716000080108643},{"id":"https://openalex.org/C150140777","wikidata":"https://www.wikidata.org/wiki/Q960648","display_name":"Point of interest","level":2,"score":0.5591999888420105},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.48739999532699585},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47589999437332153},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44859999418258667},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4374000132083893},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.42669999599456787},{"id":"https://openalex.org/C2778459138","wikidata":"https://www.wikidata.org/wiki/Q7900107","display_name":"Urban computing","level":2,"score":0.4203000068664551},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40619999170303345},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.4032999873161316},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3725999891757965},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3513999879360199},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.3319000005722046},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.31700000166893005},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.311599999666214},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2883000075817108},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2547000050544739}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3748636.3762775","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748636.3762775","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3748636.3762775","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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"},{"id":"pmid:41972096","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41972096","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ... ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems : ACM GIS. ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:13070009","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13070009/","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13070009/pdf/nihms-2157164.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc ACM SIGSPATIAL Int Conf Adv Inf","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1145/3748636.3762775","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748636.3762775","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3748636.3762775","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1040419177","display_name":null,"funder_award_id":"R01 LM014026","funder_id":"https://openalex.org/F4320337372","funder_display_name":"U.S. National Library of Medicine"},{"id":"https://openalex.org/G3035983872","display_name":null,"funder_award_id":"DMS-2428039","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4320688842","display_name":"SCC-IRG JST: Hyperlocal Risk Monitoring and Pandemic Preparedness through Privacy-Enhanced Mobility and Social Interactions Analysis","funder_award_id":"2125530","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G653847259","display_name":"SCC-IRG Track 2: Food Environment Dynamics (FED): Leveraging AI and Human Mobility Data to Address Disparities in Food Access and Improve Americans' Diets","funder_award_id":"2427150","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8034736573","display_name":"ATD: Multifaceted Large Trajectory Model for Individual and Group Anomalous Behavior Detection from Spatiotemporal Data","funder_award_id":"2428039","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8871997813","display_name":null,"funder_award_id":"R01LM014026","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G8986310910","display_name":null,"funder_award_id":"CNS-2125530","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337372","display_name":"U.S. National Library of Medicine","ror":"https://ror.org/0060t0j89"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4417283681.pdf","grobid_xml":"https://content.openalex.org/works/W4417283681.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1572856678","https://openalex.org/W1963497083","https://openalex.org/W1969207409","https://openalex.org/W1976048611","https://openalex.org/W1987706465","https://openalex.org/W1992087792","https://openalex.org/W2005988094","https://openalex.org/W2054564044","https://openalex.org/W2090702599","https://openalex.org/W2108335620","https://openalex.org/W2256145955","https://openalex.org/W2531573559","https://openalex.org/W2767923185","https://openalex.org/W2910992039","https://openalex.org/W2963423786","https://openalex.org/W3034354696","https://openalex.org/W4285827226","https://openalex.org/W4292387266","https://openalex.org/W4404106049","https://openalex.org/W4404396605","https://openalex.org/W4404611855"],"related_works":[],"abstract_inverted_index":{"Accurately":[0],"attributing":[1],"user":[2,136],"visits":[3,166],"to":[4,29,36,147,159],"specific":[5],"Points":[6],"of":[7,47,118],"Interest":[8],"(POIs)":[9],"is":[10,76],"a":[11,58,66,90,115,161],"foundational":[12],"task":[13],"for":[14,80,94,216],"mobility":[15,137,191,223],"analytics,":[16],"personalized":[17],"services,":[18],"marketing":[19],"and":[20,42,96,125,132,138,164,172,201,240],"urban":[21,50],"planning.":[22],"However,":[23],"POI":[24,83,98,130,242],"attribution":[25,187],"remains":[26],"challenging":[27,233],"due":[28],"GPS":[30],"inaccuracies,":[31],"typically":[32],"ranging":[33],"from":[34,129,135],"2":[35],"20":[37],"meters":[38],"in":[39,49,69,188,232],"real-world":[40,217,222,234],"settings,":[41],"the":[43,143,157,168],"high":[44],"spatial":[45,121,238],"density":[46,180],"POIs":[48,64],"environments,":[51],"where":[52],"multiple":[53],"venues":[54],"can":[55],"coexist":[56],"within":[57,65],"small":[59],"radius":[60,68],"(e.g.,":[61],"over":[62,228],"50":[63],"100-meter":[67],"dense":[70,241],"city":[71],"centers).":[72],"Relying":[73],"on":[74,105,207,221],"proximity":[75],"therefore":[77],"often":[78],"insufficient":[79],"determining":[81],"which":[82],"was":[84],"actually":[85],"visited.":[86],"We":[87],"introduce":[88],"POIFormer,":[89],"novel":[91],"Transformer-based":[92],"framework":[93],"accurate":[95],"efficient":[97,186],"attribution.":[99],"Unlike":[100],"prior":[101],"approaches":[102],"that":[103],"rely":[104],"limited":[106],"spatiotemporal,":[107],"contextual,":[108],"or":[109,209],"behavioral":[110,133,175],"features,":[111],"POIFormer":[112,183],"jointly":[113,148],"models":[114],"rich":[116],"set":[117],"signals,":[119],"including":[120],"proximity,":[122],"visit":[123,170],"timing":[124],"duration,":[126],"contextual":[127],"features":[128,134],"semantics,":[131],"aggregated":[139],"crowd":[140],"behavior":[141],"patterns-using":[142],"Transformer's":[144],"self-attention":[145],"mechanism":[146],"model":[149,160],"complex":[150],"interactions":[151],"across":[152,197],"these":[153],"dimensions.":[154],"By":[155],"leveraging":[156],"Transformer":[158],"user's":[162],"past":[163],"future":[165],"(with":[167],"current":[169],"masked)":[171],"incorporating":[173],"crowd-level":[174],"patterns":[176],"through":[177],"pre-computed":[178],"kernel":[179],"estimates":[181],"(KDEs),":[182],"enables":[184],"accurate,":[185],"large,":[189],"noisy":[190],"datasets.":[192],"Its":[193],"architecture":[194],"supports":[195],"generalization":[196],"diverse":[198],"data":[199,211],"sources":[200],"geographic":[202],"contexts":[203],"while":[204],"avoiding":[205],"reliance":[206],"hard-to-access":[208],"unavailable":[210],"layers,":[212],"making":[213],"it":[214],"practical":[215],"deployment.":[218],"Extensive":[219],"experiments":[220],"datasets":[224],"demonstrate":[225],"significant":[226],"improvements":[227],"existing":[229],"baselines,":[230],"particularly":[231],"settings":[235],"characterized":[236],"by":[237],"noise":[239],"clustering.":[243]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-12-12T00:00:00"}