{"id":"https://openalex.org/W7204448641","doi":"https://doi.org/10.1080/20565607.2026.2724447","title":"Tourism-context-aware one-class anomaly detection in urban visitor movement: tourist-held-out validation and a governance framework","display_name":"Tourism-context-aware one-class anomaly detection in urban visitor movement: tourist-held-out validation and a governance framework","publication_year":2026,"publication_date":"2026-08-27","ids":{"openalex":"https://openalex.org/W7204448641","doi":"https://doi.org/10.1080/20565607.2026.2724447"},"language":"en","primary_location":{"id":"doi:10.1080/20565607.2026.2724447","doi":"https://doi.org/10.1080/20565607.2026.2724447","is_oa":false,"landing_page_url":"https://doi.org/10.1080/20565607.2026.2724447","pdf_url":null,"source":{"id":"https://openalex.org/S4210192368","display_name":"International Journal of Tourism Cities","issn_l":"2056-5607","issn":["2056-5607","2056-5615"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-b","anvur-class-a","anvur-scientific","cwts-core","fnege-4","jufo-1","norway-1","poland-40","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Tourism Cities","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5050603897","display_name":"Manohar Gosul","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Manohar Gosul","raw_affiliation_strings":["Keshav Memorial College of Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Keshav Memorial College of Engineering","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067855468","display_name":"Prakash Rokade","orcid":"https://orcid.org/0000-0002-2118-6081","observed_orcids":["https://orcid.org/0000-0002-2118-6081"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Prakash Pandharinath Rokade","raw_affiliation_strings":["SND College of Engineering & Research Center"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SND College of Engineering & Research Center","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143572741","display_name":"Sujit R. Wakchaure","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4400573236","display_name":"Amrutvahini College of Engineering","ror":"https://ror.org/05x2w9m74","country_code":"IN","type":"education","lineage":["https://openalex.org/I4400573236"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sujit R. Wakchaure","raw_affiliation_strings":["Amrutvahini College of Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amrutvahini College of Engineering","institution_ids":["https://openalex.org/I4400573236"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087713556","display_name":"Venkateswarlu Gundu","orcid":"https://orcid.org/0000-0002-4412-5054","observed_orcids":["https://orcid.org/0000-0002-4412-5054"]},"institutions":[{"id":"https://openalex.org/I875944469","display_name":"Koneru Lakshmaiah Education Foundation","ror":"https://ror.org/02k949197","country_code":"IN","type":"education","lineage":["https://openalex.org/I875944469"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Venkateswarlu Gundu","raw_affiliation_strings":["Koneru Lakshmaiah Education Foundation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Koneru Lakshmaiah Education Foundation","institution_ids":["https://openalex.org/I875944469"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148466420","display_name":"S. Dinakar Raj","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I85461943","display_name":"Saveetha University","ror":"https://ror.org/0034me914","country_code":"IN","type":"education","lineage":["https://openalex.org/I85461943"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"S. Dinakar Raj","raw_affiliation_strings":["Saveetha Institute of Medical and Technical Sciences (SIMATS)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saveetha Institute of Medical and Technical Sciences (SIMATS)","institution_ids":["https://openalex.org/I85461943"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087518291","display_name":"Yadavalli S S Sriramam","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4400009046","display_name":"SRKR Engineering College","ror":"https://ror.org/038qac964","country_code":"IN","type":"education","lineage":["https://openalex.org/I4400009046"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Yadavalli S. S. Sriramam","raw_affiliation_strings":["S.R.K.R. Engineering College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"S.R.K.R. Engineering College","institution_ids":["https://openalex.org/I4400009046"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5050603897"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.54684689,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"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":0.9965999722480774,"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":0.9965999722480774,"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/T10055","display_name":"Diverse Aspects of Tourism Research","score":0.00139999995008111,"subfield":{"id":"https://openalex.org/subfields/1409","display_name":"Tourism, Leisure and Hospitality Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.0005000000237487257,"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/one-class-anomaly-detection","display_name":"one-class anomaly detection","score":0.9599999785423279},{"id":"https://openalex.org/keywords/destination-governance","display_name":"destination governance","score":0.609000027179718},{"id":"https://openalex.org/keywords/isolation-forest","display_name":"Isolation Forest","score":0.7129999995231628},{"id":"https://openalex.org/keywords/one-class-svm","display_name":"one-class support vector machine","score":0.8009999990463257},{"id":"https://openalex.org/keywords/deep-autoencoder","display_name":"deep autoencoder","score":0.8610000014305115}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6187999844551086},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6121000051498413},{"id":"https://openalex.org/C18918823","wikidata":"https://www.wikidata.org/wiki/Q49389","display_name":"Tourism","level":2,"score":0.5931000113487244},{"id":"https://openalex.org/C48947383","wikidata":"https://www.wikidata.org/wiki/Q830719","display_name":"Visitor pattern","level":2,"score":0.5005000233650208},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4242999851703644},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.42399999499320984},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4235999882221222},{"id":"https://openalex.org/C2776687071","wikidata":"https://www.wikidata.org/wiki/Q5265193","display_name":"Destinations","level":3,"score":0.4106000065803528},{"id":"https://openalex.org/C2780224610","wikidata":"https://www.wikidata.org/wiki/Q1530061","display_name":"Credibility","level":2,"score":0.4101000130176544},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4066999852657318},{"id":"https://openalex.org/C39389867","wikidata":"https://www.wikidata.org/wiki/Q380767","display_name":"Corporate governance","level":2,"score":0.4018999934196472},{"id":"https://openalex.org/C2777548347","wikidata":"https://www.wikidata.org/wiki/Q5456937","display_name":"Flagging","level":2,"score":0.39430001378059387},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.39320001006126404},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3928000032901764},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.36489999294281006},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.35839998722076416},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.33480000495910645},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.32429999113082886},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29190000891685486},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C2781198186","wikidata":"https://www.wikidata.org/wiki/Q701521","display_name":"Collusion","level":2,"score":0.2734000086784363},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.2700999975204468},{"id":"https://openalex.org/C147494362","wikidata":"https://www.wikidata.org/wiki/Q2078905","display_name":"Troubleshooting","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.26190000772476196},{"id":"https://openalex.org/C2781162219","wikidata":"https://www.wikidata.org/wiki/Q26250693","display_name":"Replicate","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.25519999861717224},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.2515999972820282},{"id":"https://openalex.org/C154504017","wikidata":"https://www.wikidata.org/wiki/Q853614","display_name":"Identifier","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/20565607.2026.2724447","doi":"https://doi.org/10.1080/20565607.2026.2724447","is_oa":false,"landing_page_url":"https://doi.org/10.1080/20565607.2026.2724447","pdf_url":null,"source":{"id":"https://openalex.org/S4210192368","display_name":"International Journal of Tourism Cities","issn_l":"2056-5607","issn":["2056-5607","2056-5615"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-b","anvur-class-a","anvur-scientific","cwts-core","fnege-4","jufo-1","norway-1","poland-40","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Tourism Cities","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7544999718666077,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W30207540","https://openalex.org/W974480840","https://openalex.org/W1724781128","https://openalex.org/W1990322848","https://openalex.org/W2095810090","https://openalex.org/W2476338024","https://openalex.org/W2518091260","https://openalex.org/W2797297964","https://openalex.org/W2901793307","https://openalex.org/W2993851910","https://openalex.org/W3018205134","https://openalex.org/W3128215095","https://openalex.org/W3153454949","https://openalex.org/W3215686731","https://openalex.org/W4239144981","https://openalex.org/W4303579235","https://openalex.org/W4304162918","https://openalex.org/W4312673899","https://openalex.org/W4384163892","https://openalex.org/W4386168374","https://openalex.org/W4390748831","https://openalex.org/W4392901724","https://openalex.org/W4394939094","https://openalex.org/W4396214404","https://openalex.org/W4396219630","https://openalex.org/W4396872025","https://openalex.org/W4400335842","https://openalex.org/W4401977746","https://openalex.org/W4404672241","https://openalex.org/W4404704036","https://openalex.org/W4416229054","https://openalex.org/W4416720712"],"related_works":["https://openalex.org/W2795138333","https://openalex.org/W4417283674","https://openalex.org/W3160756084","https://openalex.org/W4398230672","https://openalex.org/W3005040888","https://openalex.org/W4214901440","https://openalex.org/W7046038394","https://openalex.org/W3009708754","https://openalex.org/W1640705368","https://openalex.org/W2258811412"],"abstract_inverted_index":{"Urban":[0],"destinations":[1],"increasingly":[2],"monitor":[3],"visitor":[4],"movement,":[5],"yet":[6],"it":[7],"remains":[8],"unclear":[9],"whether":[10],"complex":[11],"anomaly-detection":[12],"models":[13,32],"add":[14],"value":[15],"on":[16,56,134,141],"small":[17],"tourism":[18],"datasets,":[19],"or":[20,111,136],"how":[21,154],"statistical":[22,178],"anomalies":[23,118],"should":[24,185],"be":[25],"interpreted":[26],"for":[27,79,192],"destination":[28],"governance.":[29],"Five":[30],"one-class":[31],"\u2013":[33,48],"Isolation":[34,138],"Forest,":[35],"One-Class":[36],"Support":[37],"Vector":[38],"Machine,":[39],"K-Means,":[40],"a":[41,45,52,85,164,170],"standard":[42],"autoencoder,":[43],"and":[44,73,96,127,146,168],"deep":[46],"autoencoder":[47],"were":[49],"evaluated":[50],"against":[51],"training-free":[53],"zone":[54,106],"rule":[55,133],"1,000":[57],"synthetic":[58,165],"records":[59],"from":[60,180],"284":[61],"tourist":[62,71],"identifiers,":[63],"using":[64],"five-fold":[65],"GroupKFold":[66],"that":[67,176],"held":[68],"out":[69],"complete":[70],"identifiers":[72],"an":[74,155],"inner":[75],"tourist-disjoint":[76],"validation":[77],"set":[78],"thresholds.":[80],"Robustness":[81],"was":[82],"assessed":[83],"through":[84],"tourist-clustered":[86],"paired":[87],"randomisation":[88],"test,":[89],"cyclic-hour":[90],"ablation,":[91],"threshold":[92],"analysis,":[93],"prevalence":[94],"bootstrapping":[95],"standardised":[97],"sensor-noise":[98],"tests.":[99],"Anomaly":[100],"labels":[101],"proved":[102],"largely":[103],"determined":[104],"by":[105],"designation:":[107],"flagging":[108],"every":[109],"Restricted-":[110],"Sensitive-zone":[112],"record":[113],"recovered":[114],"107":[115],"of":[116,163,173,198],"109":[117],"(recall":[119],"0.981":[120],"\u00b1":[121,125,144,149],"0.026;":[122],"F1":[123],"0.545":[124],"0.047),":[126],"no":[128],"learned":[129],"model":[130],"surpassed":[131],"this":[132],"recall":[135],"F1.":[137],"Forest":[139],"led":[140],"accuracy":[142],"(0.890":[143],"0.027)":[145],"ROC-AUC":[147],"(0.920":[148],"0.025).":[150],"The":[151],"findings":[152],"show":[153],"apparently":[156],"demanding":[157],"benchmark":[158],"can":[159],"chiefly":[160],"reward":[161],"recovery":[162],"labelling":[166],"rule,":[167],"support":[169],"relational":[171],"account":[172],"anomaly":[174,188],"significance":[175],"separates":[177],"rarity":[179],"managerial":[181],"relevance.":[182],"Destination":[183],"managers":[184],"therefore":[186],"treat":[187],"scores":[189],"as":[190],"prompts":[191],"human":[193],"verification":[194],"rather":[195],"than":[196],"evidence":[197],"threat.":[199]},"counts_by_year":[],"updated_date":"2026-10-27T15:51:10.671819","created_date":"2026-08-28T00:00:00"}
