{"id":"https://openalex.org/W3163753813","doi":"https://doi.org/10.1109/tifs.2021.3081258","title":"DFraud\u00b3: Multi-Component Fraud Detection Free of Cold-Start","display_name":"DFraud\u00b3: Multi-Component Fraud Detection Free of Cold-Start","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3163753813","doi":"https://doi.org/10.1109/tifs.2021.3081258","mag":"3163753813"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2021.3081258","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2021.3081258","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","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/A5027731320","display_name":"Saeedreza Shehnepoor","orcid":"https://orcid.org/0000-0001-6760-4501"},"institutions":[{"id":"https://openalex.org/I177877127","display_name":"University of Western Australia","ror":"https://ror.org/047272k79","country_code":"AU","type":"education","lineage":["https://openalex.org/I177877127"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Saeedreza Shehnepoor","raw_affiliation_strings":["School of Electrical, Electronic and Computer Engineering, The University of Western Australia, Perth, WA, Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical, Electronic and Computer Engineering, The University of Western Australia, Perth, WA, Australia","institution_ids":["https://openalex.org/I177877127"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017213156","display_name":"Roberto Togneri","orcid":"https://orcid.org/0000-0002-3778-4633"},"institutions":[{"id":"https://openalex.org/I177877127","display_name":"University of Western Australia","ror":"https://ror.org/047272k79","country_code":"AU","type":"education","lineage":["https://openalex.org/I177877127"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Roberto Togneri","raw_affiliation_strings":["School of Electrical, Electronic and Computer Engineering, The University of Western Australia, Perth, WA, Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical, Electronic and Computer Engineering, The University of Western Australia, Perth, WA, Australia","institution_ids":["https://openalex.org/I177877127"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100641142","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0002-7409-0948"},"institutions":[{"id":"https://openalex.org/I177877127","display_name":"University of Western Australia","ror":"https://ror.org/047272k79","country_code":"AU","type":"education","lineage":["https://openalex.org/I177877127"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["The University of Western Australia, Perth, WA, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Western Australia, Perth, WA, Australia","institution_ids":["https://openalex.org/I177877127"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009750573","display_name":"Mohammed Bennamoun","orcid":"https://orcid.org/0000-0002-6603-3257"},"institutions":[{"id":"https://openalex.org/I177877127","display_name":"University of Western Australia","ror":"https://ror.org/047272k79","country_code":"AU","type":"education","lineage":["https://openalex.org/I177877127"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Mohammed Bennamoun","raw_affiliation_strings":["The University of Western Australia, Perth, WA, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Western Australia, Perth, WA, Australia","institution_ids":["https://openalex.org/I177877127"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5027731320"],"corresponding_institution_ids":["https://openalex.org/I177877127"],"apc_list":null,"apc_paid":null,"fwci":4.2578,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.94532333,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"16","issue":null,"first_page":"3456","last_page":"3468"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9997000098228455,"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/T12519","display_name":"Cybercrime and Law Enforcement Studies","score":0.9980000257492065,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9937000274658203,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8217196464538574},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.7034832239151001},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5197693705558777},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40151476860046387},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3943358063697815},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.339539498090744},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3285368084907532},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.21942439675331116}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8217196464538574},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.7034832239151001},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5197693705558777},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40151476860046387},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3943358063697815},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.339539498090744},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3285368084907532},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.21942439675331116},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tifs.2021.3081258","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2021.3081258","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:publications/72dc7e6c-83f0-436f-8462-21bb8dbe4ab0","is_oa":false,"landing_page_url":"https://dblp.org/db/journals/tifs/tifs16.html#ShehnepoorTLB21","pdf_url":null,"source":{"id":"https://openalex.org/S4306402492","display_name":"UWA Profiles and Research Repository (UWA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I177877127","host_organization_name":"The University of Western Australia","host_organization_lineage":["https://openalex.org/I177877127"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Shehnepoor, S, Togneri, R, Liu, W & Bennamoun, M 2021, 'DFraud\u00b3: Multi-Component Fraud Detection Free of Cold-Start. Multi-Component Fraud Detection free of Cold-start', IEEE Transactions on Information Forensics and Security, vol. 16, 9435380, pp. 3456-3468. https://doi.org/10.1109/TIFS.2021.3081258","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.8100000023841858}],"awards":[],"funders":[{"id":"https://openalex.org/F4320315885","display_name":"Australian Government","ror":"https://ror.org/0314h5y94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1614298861","https://openalex.org/W1975563293","https://openalex.org/W1998871422","https://openalex.org/W2010921004","https://openalex.org/W2047756776","https://openalex.org/W2064058256","https://openalex.org/W2127795553","https://openalex.org/W2137165445","https://openalex.org/W2138781105","https://openalex.org/W2154851992","https://openalex.org/W2160338921","https://openalex.org/W2187131616","https://openalex.org/W2187846933","https://openalex.org/W2251939518","https://openalex.org/W2348679751","https://openalex.org/W2535373932","https://openalex.org/W2569238137","https://openalex.org/W2591749048","https://openalex.org/W2618063639","https://openalex.org/W2624431344","https://openalex.org/W2730363704","https://openalex.org/W2757179985","https://openalex.org/W2783466287","https://openalex.org/W2795061970","https://openalex.org/W2797657100","https://openalex.org/W2799022545","https://openalex.org/W2810845273","https://openalex.org/W2865829684","https://openalex.org/W2890697686","https://openalex.org/W2896457183","https://openalex.org/W2962739339","https://openalex.org/W2963220343","https://openalex.org/W2963341956","https://openalex.org/W2970597249","https://openalex.org/W2987064932","https://openalex.org/W3008406962","https://openalex.org/W3098653001","https://openalex.org/W3104097132","https://openalex.org/W3138539452","https://openalex.org/W3155306702","https://openalex.org/W4294558607","https://openalex.org/W6636510571","https://openalex.org/W6678830454","https://openalex.org/W6691459498","https://openalex.org/W6738964360","https://openalex.org/W6753801499","https://openalex.org/W6755207826","https://openalex.org/W6763701032","https://openalex.org/W6792565966","https://openalex.org/W6793764510"],"related_works":["https://openalex.org/W2357256365","https://openalex.org/W2348502264","https://openalex.org/W2365486383","https://openalex.org/W2362059367","https://openalex.org/W2901443725","https://openalex.org/W2350084742","https://openalex.org/W2357988862","https://openalex.org/W1855558850","https://openalex.org/W2353819887","https://openalex.org/W1852677413"],"abstract_inverted_index":{"Fraud":[0],"review":[1,55,89,112],"detection":[2,26],"is":[3,13,143],"a":[4,14,25,33,39,54,75,88,92,99,210],"hot":[5],"research":[6],"topic":[7],"in":[8,66],"recent":[9],"years.":[10],"The":[11],"Cold-start":[12],"particularly":[15],"new":[16,34,148],"but":[17],"significant":[18,211],"problem":[19],"referring":[20],"to":[21,28,46,102,125,137],"the":[22,30,48,51,62,71,111,127,195,217,220],"failure":[23],"of":[24,32,50,53,64,74,117,158,197,214,219],"system":[27,90],"recognize":[29],"authenticity":[31],"user.":[35],"State-of-the-art":[36],"solutions":[37],"employ":[38],"translational":[40],"knowledge":[41],"graph":[42,107,122],"embedding":[43],"approach":[44,199],"(TransE)":[45],"model":[47,87],"interaction":[49],"components":[52],"system.":[56],"However,":[57],"these":[58],"approaches":[59],"suffer":[60],"from":[61],"limitation":[63],"TransE":[65],"handling":[67],"N-1":[68],"relations":[69],"and":[70,105,191],"narrow":[72],"scope":[73],"single":[76],"classification":[77],"task,":[78],"i.e.,":[79,147],"detecting":[80,164],"fraudsters":[81,149],"only.":[82],"In":[83,154,182],"this":[84,155],"paper,":[85],"we":[86,185],"as":[91],"Heterogeneous":[93],"Information":[94],"Network":[95],"(HIN)":[96],"which":[97,134],"enables":[98],"unique":[100],"representation":[101],"every":[103],"component":[104],"performs":[106],"inductive":[108],"learning":[109],"on":[110,161,222],"data":[113],"through":[114],"aggregating":[115],"features":[116],"nearby":[118],"nodes.":[119],"HIN":[120],"with":[121,131,145,150],"induction":[123],"helps":[124],"address":[126],"camouflage":[128],"issue":[129],"(fraudsters":[130],"genuine":[132,151],"reviews)":[133],"has":[135],"shown":[136],"be":[138],"more":[139],"severe":[140],"when":[141],"it":[142],"coupled":[144],"cold-start,":[146],"first":[152],"reviews.":[153],"research,":[156],"instead":[157],"focusing":[159],"only":[160],"one":[162],"component,":[163,178],"either":[165],"fraud":[166,169,188],"reviews":[167],"or":[168],"users":[170],"(fraudsters),":[171],"vector":[172],"representations":[173],"are":[174],"learned":[175],"for":[176],"each":[177],"enabling":[179],"multi-component":[180],"classification.":[181],"other":[183],"words,":[184],"can":[186],"detect":[187],"reviews,":[189],"fraudsters,":[190],"fraud-targeted":[192],"items,":[193],"thus":[194],"name":[196],"our":[198],"DFraud":[200,205],"<sup":[201,206],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[202,207],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">3</sup>":[203,208],".":[204],"demonstrates":[209],"accuracy":[212],"increase":[213],"13%":[215],"over":[216],"state":[218],"art":[221],"Yelp.":[223]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
