{"id":"https://openalex.org/W3033117456","doi":"https://doi.org/10.1145/3385809","title":"Coupled IGMM-GANs with Applications to Anomaly Detection in Human Mobility Data","display_name":"Coupled IGMM-GANs with Applications to Anomaly Detection in Human Mobility Data","publication_year":2020,"publication_date":"2020-06-03","ids":{"openalex":"https://openalex.org/W3033117456","doi":"https://doi.org/10.1145/3385809","mag":"3033117456"},"language":"en","primary_location":{"id":"doi:10.1145/3385809","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3385809","pdf_url":null,"source":{"id":"https://openalex.org/S2503711797","display_name":"ACM Transactions on Spatial Algorithms and Systems","issn_l":"2374-0353","issn":["2374-0353","2374-0361"],"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 Transactions on Spatial Algorithms and Systems","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/A5089750404","display_name":"Daniel Smolyak","orcid":"https://orcid.org/0000-0003-3860-2181"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Smolyak","raw_affiliation_strings":["University of Maryland, College Park, MD"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, MD","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084250568","display_name":"Kathryn Gray","orcid":null},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kathryn Gray","raw_affiliation_strings":["University of Colorado, Linden St. Tucson, AZ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Colorado, Linden St. Tucson, AZ","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044176153","display_name":"Sarkhan Badirli","orcid":"https://orcid.org/0000-0001-8440-6830"},"institutions":[{"id":"https://openalex.org/I135191193","display_name":"University of Indianapolis","ror":"https://ror.org/052133d12","country_code":"US","type":"education","lineage":["https://openalex.org/I135191193"]},{"id":"https://openalex.org/I55769427","display_name":"Indiana University \u2013 Purdue University Indianapolis","ror":"https://ror.org/05gxnyn08","country_code":"US","type":"education","lineage":["https://openalex.org/I55769427","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sarkhan Badirli","raw_affiliation_strings":["Indiana University--Purdue University Indianapolis, Indianapolis, IN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indiana University--Purdue University Indianapolis, Indianapolis, IN","institution_ids":["https://openalex.org/I135191193","https://openalex.org/I55769427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080879125","display_name":"George Mohler","orcid":"https://orcid.org/0000-0003-4293-5106"},"institutions":[{"id":"https://openalex.org/I135191193","display_name":"University of Indianapolis","ror":"https://ror.org/052133d12","country_code":"US","type":"education","lineage":["https://openalex.org/I135191193"]},{"id":"https://openalex.org/I55769427","display_name":"Indiana University \u2013 Purdue University Indianapolis","ror":"https://ror.org/05gxnyn08","country_code":"US","type":"education","lineage":["https://openalex.org/I55769427","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George Mohler","raw_affiliation_strings":["Indiana University--Purdue University Indianapolis, Indianapolis, IN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indiana University--Purdue University Indianapolis, Indianapolis, IN","institution_ids":["https://openalex.org/I135191193","https://openalex.org/I55769427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.4717,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.91265265,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"6","issue":"4","first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9957000017166138,"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/anomaly-detection","display_name":"Anomaly detection","score":0.8498363494873047},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7560743093490601},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5361732244491577},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5325011014938354},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.4909835159778595},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4883870482444763},{"id":"https://openalex.org/keywords/mobility-model","display_name":"Mobility model","score":0.41342419385910034},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3956355154514313},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37379971146583557},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3714509606361389},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.11350300908088684}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8498363494873047},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7560743093490601},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5361732244491577},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5325011014938354},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.4909835159778595},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4883870482444763},{"id":"https://openalex.org/C191485582","wikidata":"https://www.wikidata.org/wiki/Q6887309","display_name":"Mobility model","level":2,"score":0.41342419385910034},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3956355154514313},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37379971146583557},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3714509606361389},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.11350300908088684},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3385809","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3385809","pdf_url":null,"source":{"id":"https://openalex.org/S2503711797","display_name":"ACM Transactions on Spatial Algorithms and Systems","issn_l":"2374-0353","issn":["2374-0353","2374-0361"],"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 Transactions on Spatial Algorithms and Systems","raw_type":"journal-article"},{"id":"pmh:oai:scholarworks.indianapolis.iu.edu:1805/28325","is_oa":false,"landing_page_url":"https://scholarworks.indianapolis.iu.edu/bitstreams/43c8118b-d6c3-4193-bc8e-0bcee96e3187/download","pdf_url":null,"source":{"id":"https://openalex.org/S4306400987","display_name":"IUScholarWorks (Indiana University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I592451","host_organization_name":"Indiana University","host_organization_lineage":["https://openalex.org/I592451"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Author","raw_type":"Article"},{"id":"pmh:oai:scholarworks.iupui.edu:1805/28325","is_oa":false,"landing_page_url":"https://hdl.handle.net/1805/28325","pdf_url":null,"source":{"id":"https://openalex.org/S4306400987","display_name":"IUScholarWorks (Indiana University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I592451","host_organization_name":"Indiana University","host_organization_lineage":["https://openalex.org/I592451"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Author","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G6852126538","display_name":null,"funder_award_id":"REU-1343123, SCC-1737585, ATD-1737996","funder_id":"https://openalex.org/F4320309856","funder_display_name":"National Youth Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309856","display_name":"National Youth Science Foundation","ror":"https://ror.org/054yz2f06"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1626398438","https://openalex.org/W1968701380","https://openalex.org/W1999110238","https://openalex.org/W2054242744","https://openalex.org/W2074739868","https://openalex.org/W2084335476","https://openalex.org/W2093855404","https://openalex.org/W2099471712","https://openalex.org/W2120636621","https://openalex.org/W2136317921","https://openalex.org/W2136975357","https://openalex.org/W2140251882","https://openalex.org/W2187089797","https://openalex.org/W2205813773","https://openalex.org/W2286343943","https://openalex.org/W2412320034","https://openalex.org/W2584755547","https://openalex.org/W2599354622","https://openalex.org/W2785469625","https://openalex.org/W2787947370","https://openalex.org/W2808478781","https://openalex.org/W2889205371","https://openalex.org/W2913814504","https://openalex.org/W2962816100","https://openalex.org/W2963001155","https://openalex.org/W2963045681","https://openalex.org/W2963761396","https://openalex.org/W2971198513","https://openalex.org/W2983588865"],"related_works":["https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2806741695","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W1598471830","https://openalex.org/W3107369729","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160"],"abstract_inverted_index":{"Detecting":[0],"anomalous":[1,40,179],"activity":[2],"in":[3,21,36],"human":[4,41,121,142,195],"mobility":[5,122,196],"data":[6,49,123],"has":[7],"a":[8,44,75,134,169],"number":[9],"of":[10,39,46,59,133,141,172],"applications,":[11],"including":[12],"road":[13],"hazard":[14],"sensing,":[15],"telematics-based":[16],"insurance,":[17],"and":[18,24,55,65,124,185],"fraud":[19],"detection":[20,88,160,192],"taxi":[22],"services":[23],"ride":[25],"sharing.":[26],"In":[27],"this":[28,101],"article,":[29],"we":[30,82,103,144,175],"address":[31],"two":[32],"challenges":[33],"that":[34,84,152,174],"arise":[35],"the":[37,57,131,139],"study":[38],"trajectories:":[42],"(1)":[43],"lack":[45],"ground":[47],"truth":[48],"on":[50,62,138,193],"what":[51],"defines":[52],"an":[53,105],"anomaly":[54,87,128,159,191],"(2)":[56],"dependence":[58],"existing":[60,85,158,189],"methods":[61],"significant":[63],"pre-processing":[64],"feature":[66],"engineering.":[67],"Although":[68],"generative":[69,135],"adversarial":[70],"networks":[71],"(GANs)":[72],"seem":[73],"like":[74],"natural":[76,170],"fit":[77],"for":[78,168,177],"addressing":[79],"these":[80],"challenges,":[81],"find":[83],"GAN-based":[86],"algorithms":[89],"perform":[90],"poorly":[91],"due":[92],"to":[93,96,116,147,156],"their":[94],"inability":[95],"handle":[97],"multimodal":[98,127,164],"patterns.":[99],"For":[100],"purpose,":[102],"introduce":[104],"infinite":[106],"Gaussian":[107],"mixture":[108],"model":[109],"coupled":[110],"with":[111,199],"(bidirectional)":[112],"GANs\u2014IGMM-GAN\u2014that":[113],"is":[114],"able":[115,146],"generate":[117,148],"synthetic,":[118],"yet":[119],"realistic,":[120],"simultaneously":[125],"facilitates":[126],"detection.":[129],"Through":[130],"estimation":[132],"probability":[136],"density":[137,165],"space":[140],"trajectories,":[143],"are":[145],"realistic":[149],"synthetic":[150],"datasets":[151],"can":[153],"be":[154],"used":[155],"benchmark":[157],"methods.":[161],"The":[162],"estimated":[163],"also":[166],"allows":[167],"definition":[171],"outlier":[173],"use":[176],"detecting":[178],"trajectories.":[180],"We":[181],"illustrate":[182],"our":[183],"methodology":[184],"its":[186],"improvement":[187],"over":[188],"GAN":[190],"several":[194],"datasets,":[197],"along":[198],"MNIST.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}
