{"id":"https://openalex.org/W4285310357","doi":"https://doi.org/10.1109/tbdata.2022.3172060","title":"LongArms: Fraud Prediction in Online Lending Services Using Sparse Knowledge Graph","display_name":"LongArms: Fraud Prediction in Online Lending Services Using Sparse Knowledge Graph","publication_year":2022,"publication_date":"2022-05-03","ids":{"openalex":"https://openalex.org/W4285310357","doi":"https://doi.org/10.1109/tbdata.2022.3172060"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2022.3172060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2022.3172060","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/A5100417007","display_name":"Cheng Wang","orcid":"https://orcid.org/0000-0002-4752-0316"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Cheng Wang","raw_affiliation_strings":["Shanghai Artificial Intelligence Laboratory, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-4752-0316","affiliations":[{"raw_affiliation_string":"Shanghai Artificial Intelligence Laboratory, Shanghai, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054508795","display_name":"Hangyu Zhu","orcid":"https://orcid.org/0000-0001-7221-9130"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]},{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hangyu Zhu","raw_affiliation_strings":["Department of Computer Science and Engineering, Tongji University, Shanghai, China","Key Laboratory of Embedded System and Service Computing, Ministry of Education, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-7221-9130","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]},{"raw_affiliation_string":"Key Laboratory of Embedded System and Service Computing, Ministry of Education, Shanghai, China","institution_ids":["https://openalex.org/I1327237609"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102602201","display_name":"Ruixin Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]},{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruixin Hu","raw_affiliation_strings":["Department of Computer Science and Engineering, Tongji University, Shanghai, China","Key Laboratory of Embedded System and Service Computing, Ministry of Education, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]},{"raw_affiliation_string":"Key Laboratory of Embedded System and Service Computing, Ministry of Education, Shanghai, China","institution_ids":["https://openalex.org/I1327237609"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100448560","display_name":"Rui Li","orcid":"https://orcid.org/0000-0002-8686-500X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Li","raw_affiliation_strings":["School of Computer Science and Technology, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-8686-500X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066099338","display_name":"Changjun Jiang","orcid":"https://orcid.org/0000-0003-0637-9317"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]},{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changjun Jiang","raw_affiliation_strings":["Department of Computer Science and Engineering, Tongji University, Shanghai, China","Key Laboratory of Embedded System and Service Computing, Ministry of Education, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-0637-9317","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]},{"raw_affiliation_string":"Key Laboratory of Embedded System and Service Computing, Ministry of Education, Shanghai, China","institution_ids":["https://openalex.org/I1327237609"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100417007"],"corresponding_institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"],"apc_list":null,"apc_paid":null,"fwci":1.3873,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.84175291,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"9","issue":"2","first_page":"758","last_page":"772"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9958999752998352,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9944000244140625,"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":0.6951377987861633},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4556063711643219},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4110921621322632},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37274956703186035},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33287838101387024},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.30460378527641296}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6951377987861633},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4556063711643219},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4110921621322632},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37274956703186035},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33287838101387024},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.30460378527641296}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tbdata.2022.3172060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2022.3172060","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":[{"score":0.8100000023841858,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G1754873590","display_name":null,"funder_award_id":"61972287","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2290276069","display_name":null,"funder_award_id":"22120210524","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W614715210","https://openalex.org/W1971421925","https://openalex.org/W1977009091","https://openalex.org/W1977556410","https://openalex.org/W1994948399","https://openalex.org/W2052869084","https://openalex.org/W2083620785","https://openalex.org/W2095293504","https://openalex.org/W2124351162","https://openalex.org/W2138621811","https://openalex.org/W2160642098","https://openalex.org/W2165835468","https://openalex.org/W2230049528","https://openalex.org/W2295598076","https://openalex.org/W2296034778","https://openalex.org/W2323738766","https://openalex.org/W2512496029","https://openalex.org/W2533835508","https://openalex.org/W2558192069","https://openalex.org/W2599962950","https://openalex.org/W2730363704","https://openalex.org/W2766945858","https://openalex.org/W2768675614","https://openalex.org/W2773309814","https://openalex.org/W2786577118","https://openalex.org/W2800791174","https://openalex.org/W2801308643","https://openalex.org/W2804847616","https://openalex.org/W2805473258","https://openalex.org/W2883528737","https://openalex.org/W2885321846","https://openalex.org/W2886462128","https://openalex.org/W2900547346","https://openalex.org/W2903718489","https://openalex.org/W2912788434","https://openalex.org/W2944842185","https://openalex.org/W2945876440","https://openalex.org/W2950289837","https://openalex.org/W2954152666","https://openalex.org/W2955991312","https://openalex.org/W2968404378","https://openalex.org/W2972156159","https://openalex.org/W3009901425","https://openalex.org/W3012979415","https://openalex.org/W3023056190","https://openalex.org/W3048930936","https://openalex.org/W3080686571","https://openalex.org/W3094291586","https://openalex.org/W3099064659","https://openalex.org/W3100821813","https://openalex.org/W3104412073","https://openalex.org/W3132705062","https://openalex.org/W3149900634","https://openalex.org/W3159333674","https://openalex.org/W3177385106","https://openalex.org/W4205695064","https://openalex.org/W4213251304","https://openalex.org/W4231029117","https://openalex.org/W4238530616","https://openalex.org/W4239510810"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W4306742369","https://openalex.org/W4303457083","https://openalex.org/W2951359407","https://openalex.org/W2124566234","https://openalex.org/W3136979370","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2904126538","https://openalex.org/W2963043350"],"abstract_inverted_index":{"Gang":[0],"fraud,":[1],"the":[2,17,68,90,94,135,147,183,193,202,218,255,279],"major":[3],"and":[4,44,56,76,104,187,239],"primary":[5],"security":[6],"issue":[7],"in":[8,201],"online":[9,28],"lending":[10,29,264],"services,":[11],"can":[12,168],"be":[13],"efficiently":[14,245],"solved":[15],"by":[16,92,134,216,254],"data-driven":[18],"paradigm":[19],"that":[20,37,131],"is":[21,35,222,252],"recognized":[22],"as":[23],"a":[24,112,152,212,258,262,269],"promising":[25],"solution":[26],"for":[27,172,244],"gang":[30,199,247],"fraud":[31,47,200],"prediction.":[32],"However,":[33],"it":[34],"challenging":[36],"such":[38],"predictions":[39],"need":[40],"to":[41,126,145,197],"detect":[42],"evolving":[43],"increasingly":[45],"impalpable":[46],"patterns":[48],"based":[49,191],"on":[50,111,177,192,257],"low-quality":[51],"data,":[52],"i.e.,":[53],"very":[54],"preliminary":[55],"coarse":[57],"applicant":[58,138],"information.":[59,143],"The":[60,249],"technical":[61],"difficulty":[62],"mainly":[63,88],"stems":[64],"from":[65,261],"two":[66],"factors:":[67],"extreme":[69],"<italic":[70,77,99,105,158,227,231,235,240,275],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[71,78,100,106,159,228,232,236,241,276],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">deficiency":[72],"of":[73,80,96,122,137,204,206,224],"information":[74],"associations</i>":[75,103,109],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">weakness":[79],"data":[81,207],"labels</i>":[82],".":[83],"In":[84],"this":[85],"work,":[86],"we":[87,116,150,181,210,267],"address":[89,124,141],"challenges":[91],"enhancing":[93],"utility":[95],"associations":[97,130,196],"(i.e.,":[98],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">recovering":[101],"missing":[102],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">mining":[107],"underlying":[108],")":[110],"knowledge":[113],"graph.":[114],"Specifically,":[115],"first":[117],"propose":[118,211],"an":[119],"efficient":[120],"method":[121],"Chinese":[123],"disambiguation":[125],"recover":[127],"some":[128],"critical":[129],"are":[132],"broken":[133],"ambiguity":[136],"information,":[139],"e.g.,":[140],"related":[142],"Then,":[144],"mine":[146],"implicit":[148],"associations,":[149],"design":[151],"novel":[153],"association":[154],"representation":[155],"method,":[156],"called":[157,214],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Adaptive":[160],"Connected":[161],"Component":[162],"Embedding":[163],"Simplification":[164],"Scheme</i>":[165],"(ACCESS),":[166],"which":[167,221],"adaptively":[169],"implement":[170],"embedding":[171],"different":[173],"connected":[174],"components":[175],"depending":[176],"their":[178],"sizes.":[179],"Finally,":[180],"adopt":[182],"graph":[184],"clustering":[185],"algorithms":[186],"devised":[188],"predicting":[189,246],"schemes":[190],"above":[194,219],"enhanced":[195],"predict":[198],"case":[203],"weakness":[205],"labels.":[208],"Moreover,":[209],"framework":[213],"RMCP":[215,280],"integrating":[217],"techniques,":[220],"consists":[223],"four":[225],"steps:":[226],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Recovering</i>":[229],",":[230,234,238,243],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Mining</i>":[233],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Clustering</i>":[237],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Predicting</i>":[242],"fraud.":[248],"good":[250],"performance":[251],"validated":[253],"experiments":[256],"real-world":[259],"dataset":[260],"commercial":[263],"company.":[265],"Meanwhile,":[266],"provide":[268],"visual":[270],"decision":[271],"support":[272],"system":[273],"named":[274],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">LongArms</i>":[277],"over":[278],"framework.":[281]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
