{"id":"https://openalex.org/W4388471963","doi":"https://doi.org/10.1145/3615898.3628256","title":"Optimal Risk-aware POI Recommendations during Epidemics","display_name":"Optimal Risk-aware POI Recommendations during Epidemics","publication_year":2023,"publication_date":"2023-11-07","ids":{"openalex":"https://openalex.org/W4388471963","doi":"https://doi.org/10.1145/3615898.3628256"},"language":"en","primary_location":{"id":"doi:10.1145/3615898.3628256","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3615898.3628256","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology","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/A5057059823","display_name":"Nina Yanin","orcid":"https://orcid.org/0000-0001-7279-766X"},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Nina Yanin","raw_affiliation_strings":["York University -- Toronto, Ontario, Canada"],"raw_orcid":"https://orcid.org/0000-0001-7279-766X","affiliations":[{"raw_affiliation_string":"York University -- Toronto, Ontario, Canada","institution_ids":["https://openalex.org/I192455969"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008923918","display_name":"Manos Papagelis","orcid":"https://orcid.org/0000-0003-0138-2541"},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Manos Papagelis","raw_affiliation_strings":["York University -- Toronto, Ontario, Canada"],"raw_orcid":"https://orcid.org/0000-0003-0138-2541","affiliations":[{"raw_affiliation_string":"York University -- Toronto, Ontario, Canada","institution_ids":["https://openalex.org/I192455969"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I192455969"],"apc_list":null,"apc_paid":null,"fwci":0.3562,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.74557668,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"12"},"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":0.9997000098228455,"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":0.9997000098228455,"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9980000257492065,"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"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/safer","display_name":"SAFER","score":0.7241718769073486},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.537857174873352},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.49513259530067444},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.45886465907096863},{"id":"https://openalex.org/keywords/risk-analysis","display_name":"Risk analysis (engineering)","score":0.451865017414093},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4408862590789795},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.28687405586242676},{"id":"https://openalex.org/keywords/environmental-health","display_name":"Environmental health","score":0.23857131600379944},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.21895679831504822},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.21407625079154968},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14735475182533264}],"concepts":[{"id":"https://openalex.org/C2776654903","wikidata":"https://www.wikidata.org/wiki/Q2601463","display_name":"SAFER","level":2,"score":0.7241718769073486},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.537857174873352},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.49513259530067444},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.45886465907096863},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.451865017414093},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4408862590789795},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.28687405586242676},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.23857131600379944},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.21895679831504822},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.21407625079154968},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14735475182533264},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3615898.3628256","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3615898.3628256","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1972436494","https://openalex.org/W1992120983","https://openalex.org/W2069251911","https://openalex.org/W2119790020","https://openalex.org/W2126194848","https://openalex.org/W2339065330","https://openalex.org/W2534727297","https://openalex.org/W2889079547","https://openalex.org/W2911937761","https://openalex.org/W2943793359","https://openalex.org/W3009065419","https://openalex.org/W3013215798","https://openalex.org/W3040901018","https://openalex.org/W3088611441","https://openalex.org/W3093999788","https://openalex.org/W3094817699","https://openalex.org/W3155872716","https://openalex.org/W3193634482","https://openalex.org/W4200167680","https://openalex.org/W4205338728","https://openalex.org/W4205809555","https://openalex.org/W4214915569","https://openalex.org/W4306317480","https://openalex.org/W4307472837"],"related_works":["https://openalex.org/W4230063333","https://openalex.org/W4238355463","https://openalex.org/W1498800420","https://openalex.org/W1515663861","https://openalex.org/W2085855985","https://openalex.org/W2042788600","https://openalex.org/W2007572891","https://openalex.org/W3013707207","https://openalex.org/W2108420737","https://openalex.org/W2775420868"],"abstract_inverted_index":{"The":[0,96],"movement":[1,25,59],"of":[2,8,26,72,93,98,179,200,225],"people":[3,52,81],"can":[4,18],"influence":[5,149],"the":[6,24,54,70,91,127,143,150,176,196,215,226,229,237],"spread":[7,21],"diseases,":[9],"especially":[10],"in":[11,142,168,195],"populated":[12],"areas.":[13],"While":[14],"measures":[15],"like":[16],"quarantine":[17],"curb":[19],"disease":[20],"by":[22,202,243],"restricting":[23],"those":[27],"infected,":[28],"they":[29],"come":[30],"with":[31],"socioeconomic":[32],"consequences.":[33],"Furthermore,":[34],"not":[35],"everyone":[36],"might":[37,148],"adhere":[38],"to":[39,50,57,87,239],"these":[40],"restrictions,":[41],"undermining":[42],"their":[43,58],"effectiveness.":[44],"A":[45],"more":[46],"effective":[47],"strategy":[48],"is":[49,103,130,218],"educate":[51],"on":[53,84,106,186],"risks":[55],"tied":[56],"habits":[60],"and":[61,109,182,205],"recommend":[62],"safer":[63],"options.":[64],"In":[65],"this":[66],"research,":[67],"we":[68,115],"introduce":[69],"problem":[71],"optimal":[73,216,232],"risk-aware":[74,233],"point-of-interest":[75],"(POI)":[76],"recommendations":[77,83,122],"during":[78],"epidemics,":[79],"where":[80],"get":[82],"what":[85],"POI":[86,102],"visit":[88,110],"that":[89,119,172],"reduces":[90],"risk":[92,97,129,152,199,242],"getting":[94],"infected.":[95],"infection":[99,201,241],"at":[100,153,207],"a":[101,117,193,222],"modeled":[104],"based":[105],"its":[107],"capacity":[108],"patterns":[111],"over":[112],"time.":[113],"Then,":[114],"present":[116],"method":[118,136,174,181,191,235],"provides":[120],"personalized":[121],"which,":[123],"when":[124],"universally":[125],"adopted,":[126],"overall":[128],"minimized.":[131],"Unlike":[132],"existing":[133],"strategies,":[134],"our":[135,173,190],"considers":[137],"simultaneous":[138],"user":[139],"requests":[140],"made":[141],"same":[144],"time":[145],"period,":[146],"which":[147,170],"relative":[151,197],"POIs.":[154],"An":[155],"extensive":[156],"evaluation":[157],"was":[158],"conducted,":[159],"using":[160],"real-world":[161],"data":[162],"coming":[163],"from":[164],"three":[165],"major":[166],"cities":[167],"Canada,":[169],"showed":[171],"outperforms":[175],"current":[177],"state":[178],"practice":[180],"other":[183],"sensible":[184],"baselines,":[185],"varying":[187],"settings.":[188],"Specifically,":[189],"presented":[192],"decrease":[194],"added":[198],"99.87%,":[203],"71.56%":[204],"61.54%":[206],"each":[208],"city,":[209],"respectively.":[210],"We":[211],"also":[212],"examined":[213],"how":[214],"solution":[217],"impacted":[219],"if":[220],"only":[221],"specific":[223],"portion":[224],"population":[227],"follows":[228],"recommendation.":[230],"Our":[231],"recommendation":[234],"has":[236],"potential":[238],"reduce":[240],"promoting":[244],"responsible":[245],"behaviors":[246],"within":[247],"communities.":[248]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}