{"id":"https://openalex.org/W2986704102","doi":"https://doi.org/10.1080/08839514.2019.1691341","title":"Semi-supervised Classification of Fraud Data in Commercial Auctions","display_name":"Semi-supervised Classification of Fraud Data in Commercial Auctions","publication_year":2019,"publication_date":"2019-11-14","ids":{"openalex":"https://openalex.org/W2986704102","doi":"https://doi.org/10.1080/08839514.2019.1691341","mag":"2986704102"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2019.1691341","is_oa":false,"landing_page_url":"https://doi.org/10.1080/08839514.2019.1691341","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"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/A5029196578","display_name":"Sulaf Elshaar","orcid":"https://orcid.org/0000-0003-1892-2284"},"institutions":[{"id":"https://openalex.org/I194028371","display_name":"University of Regina","ror":"https://ror.org/03dzc0485","country_code":"CA","type":"education","lineage":["https://openalex.org/I194028371"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Sulaf Elshaar","raw_affiliation_strings":["Computer Science Department, University of Regina, Regina, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Regina, Regina, Canada","institution_ids":["https://openalex.org/I194028371"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026015679","display_name":"Samira Sadaoui","orcid":"https://orcid.org/0000-0002-9887-1570"},"institutions":[{"id":"https://openalex.org/I194028371","display_name":"University of Regina","ror":"https://ror.org/03dzc0485","country_code":"CA","type":"education","lineage":["https://openalex.org/I194028371"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Samira Sadaoui","raw_affiliation_strings":["Computer Science Department, University of Regina, Regina, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Regina, Regina, Canada","institution_ids":["https://openalex.org/I194028371"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5029196578"],"corresponding_institution_ids":["https://openalex.org/I194028371"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":null,"fwci":2.0325,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.90275937,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"34","issue":"1","first_page":"47","last_page":"63"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9995999932289124,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9995999932289124,"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/T11182","display_name":"Auction Theory and Applications","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12519","display_name":"Cybercrime and Law Enforcement Studies","score":0.9563000202178955,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8616541624069214},{"id":"https://openalex.org/keywords/bidding","display_name":"Bidding","score":0.8319151401519775},{"id":"https://openalex.org/keywords/common-value-auction","display_name":"Common value auction","score":0.7881497144699097},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7532809376716614},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.60871422290802},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4992380142211914},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.43317320942878723},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4261564612388611},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4128408133983612},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38446226716041565},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3791763186454773},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.077705979347229}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8616541624069214},{"id":"https://openalex.org/C9233905","wikidata":"https://www.wikidata.org/wiki/Q3276328","display_name":"Bidding","level":2,"score":0.8319151401519775},{"id":"https://openalex.org/C163239763","wikidata":"https://www.wikidata.org/wiki/Q5153637","display_name":"Common value auction","level":2,"score":0.7881497144699097},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7532809376716614},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.60871422290802},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4992380142211914},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.43317320942878723},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4261564612388611},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4128408133983612},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38446226716041565},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3791763186454773},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.077705979347229},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/08839514.2019.1691341","is_oa":false,"landing_page_url":"https://doi.org/10.1080/08839514.2019.1691341","pdf_url":null,"source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ce6c36ec687144e2a8a39bb855fbca3e","is_oa":false,"landing_page_url":"https://doaj.org/article/ce6c36ec687144e2a8a39bb855fbca3e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 34, Iss 1, Pp 47-63 (2020)","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7900000214576721,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W58586023","https://openalex.org/W1585610988","https://openalex.org/W1594145284","https://openalex.org/W2021119487","https://openalex.org/W2052004758","https://openalex.org/W2084789837","https://openalex.org/W2120921728","https://openalex.org/W2148143831","https://openalex.org/W2480260901","https://openalex.org/W2592516822","https://openalex.org/W2742869193","https://openalex.org/W2783344919","https://openalex.org/W2807512355","https://openalex.org/W2895850111","https://openalex.org/W2897687418","https://openalex.org/W2898130023","https://openalex.org/W2898690144","https://openalex.org/W2900224610","https://openalex.org/W2910335025","https://openalex.org/W2949578283","https://openalex.org/W3102746519","https://openalex.org/W3103349515"],"related_works":["https://openalex.org/W1995388959","https://openalex.org/W2147694495","https://openalex.org/W1984203460","https://openalex.org/W1562320220","https://openalex.org/W4317548404","https://openalex.org/W3022007134","https://openalex.org/W2130553454","https://openalex.org/W2087783760","https://openalex.org/W2033364610","https://openalex.org/W2168489430"],"abstract_inverted_index":{"Given":[0],"the":[1,30,55,67,71,96,101,144,168],"magnitude":[2],"of":[3,59,61,73,126,146,205],"monetary":[4],"transactions":[5],"at":[6],"auction":[7],"sites,":[8],"they":[9],"are":[10],"very":[11],"attractive":[12],"to":[13,90,105,153,203],"fraudsters":[14,75],"and":[15,33,39,49,66,120,138,152],"scam":[16],"artists.":[17],"Shill":[18],"bidding":[19,31],"(SB)":[20],"is":[21,34,51,100],"a":[22,124,147,173,193],"severe":[23],"fraud":[24,107],"in":[25,69,180],"e-auctions,":[26],"which":[27,99],"occurs":[28],"during":[29],"period":[32],"driven":[35],"by":[36,54],"modern-day":[37],"technology":[38],"clever":[40],"scammers.":[41],"SB":[42,65,79,118,128,133,149,190,196],"does":[43],"not":[44],"produce":[45],"any":[46],"obvious":[47],"evidence,":[48],"it":[50],"often":[52],"unnoticed":[53],"victims.":[56],"The":[57],"lack":[58],"availability":[60],"training":[62,181],"datasets":[63],"for":[64,95],"difficulty":[68],"identifying":[70],"behavior":[72],"sophisticated":[74],"hinder":[76],"research":[77],"on":[78,123,163],"detection.":[80],"To":[81],"safeguard":[82],"consumers":[83],"from":[84,135],"dishonest":[85],"bidders,":[86],"we":[87,113,130,156],"were":[88],"incentivized":[89],"investigate":[91],"semi-supervised":[92],"classification":[93,108],"(SSC)":[94],"first":[97,114],"time,":[98],"most":[102],"suitable":[103],"approach":[104],"solving":[106],"problems.":[109],"In":[110],"this":[111,154],"study,":[112],"introduce":[115],"two":[116],"new":[117],"patterns,":[119,129],"then":[121],"based":[122,162],"total":[125],"nine":[127],"build":[131],"an":[132,158],"dataset":[134],"commercial":[136],"auctions":[137],"bidder":[139],"history":[140],"data.":[141],"SSC":[142,183],"requires":[143],"labeling":[145],"few":[148,194],"data":[150,164,175,191,197],"samples,":[151],"end,":[155],"propose":[157],"anomaly":[159],"detection":[160],"method":[161],"clustering.":[165],"We":[166],"addressed":[167],"skewed":[169],"class":[170],"distribution":[171],"with":[172,192],"hybrid":[174],"sampling":[176],"method.":[177],"Our":[178],"experiments":[179],"several":[182],"models":[184],"show":[185],"that":[186,204],"using":[187],"primarily":[188],"unlabeled":[189],"labeled":[195],"improves":[198],"predictive":[199],"performance":[200],"when":[201],"compared":[202],"supervised":[206],"models.":[207]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}