{"id":"https://openalex.org/W4406459090","doi":"https://doi.org/10.1109/bigdata62323.2024.10825157","title":"Context-aware Data Sampling with Reciprocal Nearest Neighbors for Fraud Classification","display_name":"Context-aware Data Sampling with Reciprocal Nearest Neighbors for Fraud Classification","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406459090","doi":"https://doi.org/10.1109/bigdata62323.2024.10825157"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825157","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825157","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-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/A5086856321","display_name":"Sharath Kumar","orcid":"https://orcid.org/0000-0001-8964-6892"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Sharath Kumar","raw_affiliation_strings":["Hitachi India Pvt Ltd,Research and Development Centre,Bangalore,India"],"affiliations":[{"raw_affiliation_string":"Hitachi India Pvt Ltd,Research and Development Centre,Bangalore,India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060285029","display_name":"Manikandan Ravikiran","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Manikandan Ravikiran","raw_affiliation_strings":["Hitachi India Pvt Ltd,Research and Development Centre,Bangalore,India"],"affiliations":[{"raw_affiliation_string":"Hitachi India Pvt Ltd,Research and Development Centre,Bangalore,India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036283540","display_name":"Nestor Mariyasagayam","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nestor Mariyasagayam","raw_affiliation_strings":["Hitachi India Pvt Ltd,Research and Development Centre,Bangalore,India"],"affiliations":[{"raw_affiliation_string":"Hitachi India Pvt Ltd,Research and Development Centre,Bangalore,India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5086856321"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3862,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.7112074,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"5184","last_page":"5191"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.992900013923645,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9925000071525574,"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":0.7444124221801758},{"id":"https://openalex.org/keywords/reciprocal","display_name":"Reciprocal","score":0.6293402314186096},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5987095236778259},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4657381772994995},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4459741413593292},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35231778025627136},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32384729385375977},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09894916415214539},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.0646330714225769}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7444124221801758},{"id":"https://openalex.org/C2777742833","wikidata":"https://www.wikidata.org/wiki/Q1964083","display_name":"Reciprocal","level":2,"score":0.6293402314186096},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5987095236778259},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4657381772994995},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4459741413593292},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35231778025627136},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32384729385375977},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09894916415214539},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0646330714225769},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825157","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825157","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.699999988079071,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2053724458","https://openalex.org/W2076188996","https://openalex.org/W2104933073","https://openalex.org/W2132791018","https://openalex.org/W2148143831","https://openalex.org/W2301363727","https://openalex.org/W2476492714","https://openalex.org/W2555973645","https://openalex.org/W2593463961","https://openalex.org/W2909043555","https://openalex.org/W2949305894","https://openalex.org/W2999829553","https://openalex.org/W3096831136","https://openalex.org/W3142358180","https://openalex.org/W4213251304","https://openalex.org/W4230014050","https://openalex.org/W4297347671","https://openalex.org/W4299296451","https://openalex.org/W4362597616","https://openalex.org/W4400762160","https://openalex.org/W6675978457","https://openalex.org/W6683804467","https://openalex.org/W6745609711","https://openalex.org/W6782850880","https://openalex.org/W6784694678","https://openalex.org/W6790279767","https://openalex.org/W6791639301","https://openalex.org/W6792576804","https://openalex.org/W6853103392","https://openalex.org/W6860196819","https://openalex.org/W6861624397","https://openalex.org/W6861715406"],"related_works":["https://openalex.org/W2391753177","https://openalex.org/W2996284460","https://openalex.org/W4298337043","https://openalex.org/W1966306316","https://openalex.org/W4285058191","https://openalex.org/W2052414331","https://openalex.org/W3003660440","https://openalex.org/W2028403663","https://openalex.org/W2735124752","https://openalex.org/W4383174144"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"Modified":[5],"ADASYN":[6],"(M-ADASYN),":[7],"an":[8,84],"oversampling":[9,23],"technique":[10],"designed":[11],"to":[12,40,98,130],"address":[13],"class":[14,51,127],"imbalance":[15],"in":[16,91],"fine-grained":[17],"fraud":[18],"classification":[19,92,108],"tasks.":[20],"Unlike":[21],"traditional":[22],"methods":[24,75],"that":[25,72],"often":[26],"generate":[27],"noisy":[28],"synthetic":[29,59],"samples":[30],"near":[31],"decision":[32],"boundaries,":[33],"M-ADASYN":[34,73,95],"incorporates":[35],"Reciprocal":[36],"Nearest":[37],"Neighbors":[38],"(RNN)":[39],"focus":[41],"on":[42],"densely":[43],"populated":[44],"minority":[45],"regions,":[46],"minimizing":[47],"overlap":[48],"with":[49],"majority":[50],"data.":[52],"This":[53],"approach":[54],"improves":[55],"the":[56],"quality":[57],"of":[58,86,119,125],"samples,":[60],"reduces":[61],"false":[62],"positives,":[63],"and":[64,80,113,133],"enhances":[65],"model":[66,104],"generalization.":[67],"Extensive":[68],"experimental":[69],"evaluation":[70],"demonstrates":[71],"outperforms":[74],"such":[76],"as":[77],"SMOTE,":[78],"ADASYN,":[79],"GAN-based":[81],"approaches,":[82],"by":[83],"average":[85],"3":[87],"percentage":[88],"points":[89],"improvement":[90],"accuracy.":[93],"Furthermore,":[94],"is":[96],"shown":[97],"reduce":[99],"training":[100],"time":[101],"while":[102],"maintaining":[103],"performance":[105],"across":[106],"multiple":[107],"models,":[109],"including":[110],"Random":[111],"Forest":[112],"LightGBM.":[114],"The":[115],"proposed":[116],"method\u2019s":[117],"integration":[118],"RNN":[120],"ensures":[121],"more":[122],"efficient":[123],"handling":[124],"extreme":[126],"imbalance,":[128],"leading":[129],"improved":[131],"accuracy":[132],"computational":[134],"efficiency.":[135]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
