{"id":"https://openalex.org/W7118535456","doi":"https://doi.org/10.48550/arxiv.2601.00075","title":"IMBWatch -- a Spatio-Temporal Graph Neural Network approach to detect Illicit Massage Business","display_name":"IMBWatch -- a Spatio-Temporal Graph Neural Network approach to detect Illicit Massage Business","publication_year":2025,"publication_date":"2025-12-31","ids":{"openalex":"https://openalex.org/W7118535456","doi":"https://doi.org/10.48550/arxiv.2601.00075"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.00075","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.00075","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2601.00075","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068552902","display_name":"Swetha Varadarajan","orcid":"https://orcid.org/0000-0002-0256-7639"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Varadarajan, Swetha","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090619610","display_name":"Abhishek Ray","orcid":"https://orcid.org/0000-0001-9963-1918"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ray, Abhishek","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5067583517","display_name":"Lumina S. Albert","orcid":"https://orcid.org/0000-0002-9118-783X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Albert, Lumina","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5068552902"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.301800012588501,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.301800012588501,"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/T12519","display_name":"Cybercrime and Law Enforcement Studies","score":0.052400000393390656,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.05209999904036522,"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/phone","display_name":"Phone","score":0.6444000005722046},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.498199999332428},{"id":"https://openalex.org/keywords/license","display_name":"License","score":0.487199991941452},{"id":"https://openalex.org/keywords/reuse","display_name":"Reuse","score":0.46779999136924744},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4366999864578247},{"id":"https://openalex.org/keywords/covert","display_name":"Covert","score":0.40610000491142273},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.3921999931335449},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3398999869823456},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.33000001311302185},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.3276999890804291}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7204999923706055},{"id":"https://openalex.org/C2778707766","wikidata":"https://www.wikidata.org/wiki/Q202064","display_name":"Phone","level":2,"score":0.6444000005722046},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.498199999332428},{"id":"https://openalex.org/C2780560020","wikidata":"https://www.wikidata.org/wiki/Q79719","display_name":"License","level":2,"score":0.487199991941452},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.46779999136924744},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4383000135421753},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4366999864578247},{"id":"https://openalex.org/C2779338814","wikidata":"https://www.wikidata.org/wiki/Q5179285","display_name":"Covert","level":2,"score":0.40610000491142273},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3921999931335449},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3596000075340271},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.35420000553131104},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3398999869823456},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.33000001311302185},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.3276999890804291},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3246999979019165},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3237999975681305},{"id":"https://openalex.org/C4216890","wikidata":"https://www.wikidata.org/wiki/Q815823","display_name":"Business model","level":2,"score":0.3165000081062317},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2996000051498413},{"id":"https://openalex.org/C118643609","wikidata":"https://www.wikidata.org/wiki/Q189210","display_name":"Web application","level":2,"score":0.29809999465942383},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.2879999876022339},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2865999937057495},{"id":"https://openalex.org/C2779041454","wikidata":"https://www.wikidata.org/wiki/Q870780","display_name":"Chatbot","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C108170787","wikidata":"https://www.wikidata.org/wiki/Q3951828","display_name":"Agency (philosophy)","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C153646914","wikidata":"https://www.wikidata.org/wiki/Q535695","display_name":"Cellular network","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C53811970","wikidata":"https://www.wikidata.org/wiki/Q5062194","display_name":"Centrality","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C22927095","wikidata":"https://www.wikidata.org/wiki/Q1784206","display_name":"Stateful firewall","level":3,"score":0.2578999996185303},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.2540000081062317},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.00075","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.00075","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2601.00075","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.00075","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.6294706463813782,"id":"https://metadata.un.org/sdg/5","display_name":"Gender equality"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Illicit":[0],"Massage":[1],"Businesses":[2],"(IMBs)":[3],"are":[4,66],"a":[5,87],"covert":[6],"and":[7,28,44,46,56,63,69,112,125,131,139,161,173,194,210,222,227],"persistent":[8],"form":[9],"of":[10,18,49,156],"organized":[11],"exploitation":[12],"that":[13,186],"operate":[14],"under":[15],"the":[16,47,73,154],"facade":[17],"legitimate":[19],"wellness":[20],"services":[21],"while":[22,127],"facilitating":[23],"human":[24],"trafficking,":[25],"sexual":[26],"exploitation,":[27],"coerced":[29],"labor.":[30],"Detecting":[31],"IMBs":[32],"is":[33,215],"difficult":[34],"due":[35],"to":[36,152,207,218,230],"encoded":[37],"digital":[38],"advertisements,":[39,108],"frequent":[40],"changes":[41],"in":[42],"personnel":[43],"locations,":[45,126],"reuse":[48],"shared":[50],"infrastructure":[51],"such":[52,119,165],"as":[53,120,166],"phone":[54,123,137,171],"numbers":[55],"addresses.":[57],"Traditional":[58],"approaches,":[59],"including":[60,105,134],"community":[61],"tips":[62],"regulatory":[64],"inspections,":[65],"largely":[67],"reactive":[68],"ineffective":[70],"at":[71],"revealing":[72],"broader":[74],"operational":[75],"networks":[76,158],"traffickers":[77],"rely":[78],"on.":[79],"To":[80],"address":[81],"these":[82],"challenges,":[83],"we":[84],"introduce":[85],"IMBWatch,":[86],"spatio-temporal":[88,130],"graph":[89,145],"neural":[90],"network":[91],"(ST-GNN)":[92],"framework":[93,143,214],"for":[94],"large-scale":[95],"IMB":[96,157],"detection.":[97],"IMBWatch":[98,187,200],"constructs":[99],"dynamic":[100],"graphs":[101],"from":[102,181],"open-source":[103,228],"intelligence,":[104],"scraped":[106],"online":[107],"business":[109],"license":[110],"records,":[111],"crowdsourced":[113],"reviews.":[114],"Nodes":[115],"represent":[116],"heterogeneous":[117],"entities":[118],"businesses,":[121],"aliases,":[122],"numbers,":[124],"edges":[128],"capture":[129],"relational":[132],"patterns,":[133],"co-location,":[135],"repeated":[136],"usage,":[138],"synchronized":[140],"advertising.":[141],"The":[142,213],"combines":[144],"convolutional":[146],"operations":[147],"with":[148,224],"temporal":[149],"attention":[150],"mechanisms":[151],"model":[153],"evolution":[155],"over":[159],"time":[160],"space,":[162],"capturing":[163],"patterns":[164],"intercity":[167],"worker":[168],"movement,":[169],"burner":[170],"rotation,":[172],"coordinated":[174],"advertising":[175],"surges.":[176],"Experiments":[177],"on":[178],"real-world":[179],"datasets":[180],"multiple":[182],"U.S.":[183],"cities":[184],"show":[185],"outperforms":[188],"baseline":[189],"models,":[190],"achieving":[191],"higher":[192],"accuracy":[193],"F1":[195],"scores.":[196],"Beyond":[197],"performance":[198],"gains,":[199],"offers":[201],"improved":[202],"interpretability,":[203],"providing":[204],"actionable":[205],"insights":[206],"support":[208,231],"proactive":[209],"targeted":[211],"interventions.":[212],"scalable,":[216],"adaptable":[217],"other":[219],"illicit":[220],"domains,":[221],"released":[223],"anonymized":[225],"data":[226],"code":[229],"reproducible":[232],"research.":[233]},"counts_by_year":[],"updated_date":"2026-01-08T20:10:11.968330","created_date":"2026-01-08T00:00:00"}
