{"id":"https://openalex.org/W4206218111","doi":"https://doi.org/10.1109/tbdata.2021.3132672","title":"MAFI: GNN-Based Multiple Aggregators and Feature Interactions Network for Fraud Detection Over Heterogeneous Graph","display_name":"MAFI: GNN-Based Multiple Aggregators and Feature Interactions Network for Fraud Detection Over Heterogeneous Graph","publication_year":2021,"publication_date":"2021-12-06","ids":{"openalex":"https://openalex.org/W4206218111","doi":"https://doi.org/10.1109/tbdata.2021.3132672"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2021.3132672","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2021.3132672","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Big Data","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/A5008181744","display_name":"Nan Jiang","orcid":"https://orcid.org/0000-0003-1712-1872"},"institutions":[{"id":"https://openalex.org/I13985625","display_name":"East China Jiaotong University","ror":"https://ror.org/05x2f1m38","country_code":"CN","type":"education","lineage":["https://openalex.org/I13985625"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Nan Jiang","raw_affiliation_strings":["College of Information Engineering, East China Jiaotong University, Nanchang, P.R. China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, East China Jiaotong University, Nanchang, P.R. China","institution_ids":["https://openalex.org/I13985625"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069188128","display_name":"Fuxian Duan","orcid":"https://orcid.org/0000-0002-6315-2787"},"institutions":[{"id":"https://openalex.org/I13985625","display_name":"East China Jiaotong University","ror":"https://ror.org/05x2f1m38","country_code":"CN","type":"education","lineage":["https://openalex.org/I13985625"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuxian Duan","raw_affiliation_strings":["College of Information Engineering, East China Jiaotong University, Nanchang, P.R. China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, East China Jiaotong University, Nanchang, P.R. China","institution_ids":["https://openalex.org/I13985625"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005165463","display_name":"Honglong Chen","orcid":"https://orcid.org/0000-0003-0739-6338"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Honglong Chen","raw_affiliation_strings":["College of Control Science and Engineering, China University of Petroleum(East China), Qingdao, P.R. China"],"affiliations":[{"raw_affiliation_string":"College of Control Science and Engineering, China University of Petroleum(East China), Qingdao, P.R. China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004584268","display_name":"Wei Huang","orcid":"https://orcid.org/0000-0002-0541-8612"},"institutions":[{"id":"https://openalex.org/I141649914","display_name":"Nanchang University","ror":"https://ror.org/042v6xz23","country_code":"CN","type":"education","lineage":["https://openalex.org/I141649914"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Huang","raw_affiliation_strings":["Department of Compute Science, Nanchang University, Nanchang, P.R. China"],"affiliations":[{"raw_affiliation_string":"Department of Compute Science, Nanchang University, Nanchang, P.R. China","institution_ids":["https://openalex.org/I141649914"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058120371","display_name":"Ximeng Liu","orcid":"https://orcid.org/0000-0002-4238-3295"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ximeng Liu","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5008181744"],"corresponding_institution_ids":["https://openalex.org/I13985625"],"apc_list":null,"apc_paid":null,"fwci":6.0592,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.96434958,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"8","issue":"4","first_page":"905","last_page":"919"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9990000128746033,"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":0.9990000128746033,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9979000091552734,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9939000010490417,"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":0.8522235155105591},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5086553692817688},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.415929913520813},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33941757678985596},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3104226291179657}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8522235155105591},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5086553692817688},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.415929913520813},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33941757678985596},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3104226291179657},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tbdata.2021.3132672","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2021.3132672","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Big Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.8100000023841858,"display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G2216787661","display_name":null,"funder_award_id":"20212ACB212002","funder_id":"https://openalex.org/F4320322665","funder_display_name":"Natural Science Foundation of Jiangxi Province"},{"id":"https://openalex.org/G3291271152","display_name":null,"funder_award_id":"U1804263","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3722181598","display_name":null,"funder_award_id":"61962022","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7086620112","display_name":null,"funder_award_id":"62062034","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8732270613","display_name":null,"funder_award_id":"62172160","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G979158640","display_name":null,"funder_award_id":"62072109","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322665","display_name":"Natural Science Foundation of Jiangxi Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W103340358","https://openalex.org/W893486657","https://openalex.org/W1888005072","https://openalex.org/W2016266039","https://openalex.org/W2064058256","https://openalex.org/W2104167780","https://openalex.org/W2136710010","https://openalex.org/W2136891251","https://openalex.org/W2154851992","https://openalex.org/W2157331557","https://openalex.org/W2348679751","https://openalex.org/W2604314403","https://openalex.org/W2618063639","https://openalex.org/W2622263826","https://openalex.org/W2782836818","https://openalex.org/W2783466287","https://openalex.org/W2788728386","https://openalex.org/W2897862648","https://openalex.org/W2907379153","https://openalex.org/W2911286998","https://openalex.org/W2945996535","https://openalex.org/W2962756421","https://openalex.org/W2962986764","https://openalex.org/W2963415211","https://openalex.org/W2964182926","https://openalex.org/W2965857891","https://openalex.org/W2966360566","https://openalex.org/W2970127247","https://openalex.org/W2984239289","https://openalex.org/W2988801199","https://openalex.org/W2997619488","https://openalex.org/W3002957251","https://openalex.org/W3004507689","https://openalex.org/W3009901425","https://openalex.org/W3012631161","https://openalex.org/W3012871709","https://openalex.org/W3012901223","https://openalex.org/W3021651554","https://openalex.org/W3022945404","https://openalex.org/W3035298482","https://openalex.org/W3068123808","https://openalex.org/W3080933176","https://openalex.org/W3099064659","https://openalex.org/W3099825604","https://openalex.org/W3102969158","https://openalex.org/W3103513278","https://openalex.org/W3104097132","https://openalex.org/W3107500918","https://openalex.org/W3124675547","https://openalex.org/W6631190155","https://openalex.org/W6690815549","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6739622702","https://openalex.org/W6739901393","https://openalex.org/W6749077313","https://openalex.org/W6765827838","https://openalex.org/W6775947557"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Recently,":[0],"Graph":[1],"Neural":[2],"Networks":[3],"(GNNs)":[4],"have":[5],"been":[6],"widely":[7],"used":[8],"for":[9],"fraud":[10,119,189,199],"detection.":[11],"GNNs":[12,38,71],"first":[13],"generate":[14],"node":[15,29],"embedding":[16,30],"by":[17,74],"aggregating":[18],"neighboring":[19],"information":[20,50,63,135],"under":[21],"different":[22,56,130,146],"relations,":[23],"and":[24,54,107,136,169],"then":[25],"use":[26],"the":[27,33,61,83,143,155,193],"final":[28],"to":[31,47,81,117,132,141,153,180],"detect":[32],"node\u2019s":[34],"suspiciousness.":[35],"However,":[36],"traditional":[37],"employing":[39],"only":[40],"a":[41,97,174],"single":[42],"type":[43],"of":[44,64,70,125,145,157],"aggregator":[45],"fail":[46],"capture":[48],"neighbor":[49,134,176],"from":[51],"multiple":[52,123],"perspectives":[53],"treating":[55],"relations":[57,131],"equally":[58],"inevitably":[59],"weakens":[60],"semantic":[62],"heterogeneous":[65,99],"graphs.":[66],"Meanwhile,":[67],"expressive":[68],"ability":[69],"is":[72,112,139,151,178],"limited":[73],"using":[75],"conventional":[76,161],"concatenating":[77],"or":[78],"averaging":[79],"operations":[80,163],"update":[82,162],"center":[84],"node.":[85],"Also,":[86,148],"camouflaged":[87,182],"entities":[88],"could":[89],"damage":[90],"GNN-based":[91,198],"models.":[92],"To":[93],"handle":[94],"these":[95],"problems,":[96],"novel":[98],"GNN":[100],"model":[101],"called":[102],"<italic":[103],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[104],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Multiple":[105],"Aggregators":[106],"Feature":[108],"Interactions":[109],"Network</i>":[110],"(MAFI)":[111],"proposed":[113,194],"in":[114],"this":[115],"paper":[116],"conduct":[118],"detection":[120],"tasks.":[121],"Concretely,":[122],"types":[124],"aggregators":[126],"are":[127,164],"applied":[128],"on":[129,186],"aggregate":[133],"aggregator-level":[137],"attention":[138,150],"utilized":[140],"learn":[142,154],"importance":[144,156],"aggregators.":[147],"relation-level":[149],"leveraged":[152],"each":[158],"relation.":[159],"Besides,":[160],"replaced":[165],"with":[166],"vector-wise":[167],"implicit":[168],"explicit":[170],"feature":[171],"interactions.":[172],"Moreover,":[173],"trainable":[175],"sampler":[177],"employed":[179],"filter":[181],"fraudsters.":[183],"Comprehensive":[184],"experiments":[185],"two":[187],"real-world":[188],"datasets":[190],"indicate":[191],"that":[192],"MAFI":[195],"outperforms":[196],"existing":[197],"detectors.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
