{"id":"https://openalex.org/W4414165683","doi":"https://doi.org/10.1109/tkde.2025.3607862","title":"Balancing Act: MDGAN for Imbalanced Tabular Data Synthesis","display_name":"Balancing Act: MDGAN for Imbalanced Tabular Data Synthesis","publication_year":2025,"publication_date":"2025-09-09","ids":{"openalex":"https://openalex.org/W4414165683","doi":"https://doi.org/10.1109/tkde.2025.3607862"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2025.3607862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2025.3607862","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"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 Knowledge and Data Engineering","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/A5080389312","display_name":"Hongwei Ding","orcid":"https://orcid.org/0000-0002-0851-1994"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongwei Ding","raw_affiliation_strings":["School of Computer and Communication Engineering, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-0851-1994","affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018752239","display_name":"Nana Huang","orcid":"https://orcid.org/0000-0003-4566-4129"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nana Huang","raw_affiliation_strings":["School of Cyberspace, Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-4566-4129","affiliations":[{"raw_affiliation_string":"School of Cyberspace, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031568841","display_name":"Qi Tao","orcid":"https://orcid.org/0000-0002-8715-6969"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Tao","raw_affiliation_strings":["School of Data Science & Engineering, South China Normal University, Guangzhou, China","School of Data Science & Engineering, South China Normal University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-8715-6969","affiliations":[{"raw_affiliation_string":"School of Data Science & Engineering, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"School of Data Science & Engineering, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043670878","display_name":"Jiaqi Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I21642278","display_name":"Ningxia University","ror":"https://ror.org/04j7b2v61","country_code":"CN","type":"education","lineage":["https://openalex.org/I21642278"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Liang","raw_affiliation_strings":["School of Advanced Interdisciplinary Studies, Ningxia University, Yinchuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Advanced Interdisciplinary Studies, Ningxia University, Yinchuan, China","institution_ids":["https://openalex.org/I21642278"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041280931","display_name":"Xiaohui Cui","orcid":"https://orcid.org/0000-0001-6079-009X"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohui Cui","raw_affiliation_strings":["School of Cyber Science and Engineering, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-6079-009X","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5080389312"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":2.9423,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.92219252,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"37","issue":"11","first_page":"6304","last_page":"6319"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.8996000289916992,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.8996000289916992,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12034","display_name":"Digital and Cyber Forensics","score":0.8949999809265137,"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/T11269","display_name":"Algorithms and Data Compression","score":0.8492000102996826,"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/oversampling","display_name":"Oversampling","score":0.8910999894142151},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7149999737739563},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.6184999942779541},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5767999887466431},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5630999803543091},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.486299991607666},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4115999937057495},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.40049999952316284}],"concepts":[{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.8910999894142151},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8166999816894531},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7149999737739563},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.6184999942779541},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6051999926567078},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5985999703407288},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5767999887466431},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5630999803543091},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.486299991607666},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4115999937057495},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.40049999952316284},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3968999981880188},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.362199991941452},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3601999878883362},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.2935999929904938},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2808000147342682},{"id":"https://openalex.org/C13926793","wikidata":"https://www.wikidata.org/wiki/Q3507155","display_name":"Group method of data handling","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2578999996185303}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2025.3607862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2025.3607862","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"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 Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4693610667","display_name":null,"funder_award_id":"F2024501021","funder_id":"https://openalex.org/F4320322163","funder_display_name":"Natural Science Foundation of Hebei Province"},{"id":"https://openalex.org/G6355133464","display_name":null,"funder_award_id":"N2423015","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320322163","display_name":"Natural Science Foundation of Hebei Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1605695115","https://openalex.org/W1994410331","https://openalex.org/W2096733369","https://openalex.org/W2104933073","https://openalex.org/W2132791018","https://openalex.org/W2148143831","https://openalex.org/W2766296277","https://openalex.org/W2963351448","https://openalex.org/W2971644666","https://openalex.org/W2971749073","https://openalex.org/W2981515171","https://openalex.org/W3104109355","https://openalex.org/W3111875476","https://openalex.org/W3112293331","https://openalex.org/W3119162813","https://openalex.org/W3125241865","https://openalex.org/W3127368173","https://openalex.org/W3135420375","https://openalex.org/W3157699413","https://openalex.org/W3197592613","https://openalex.org/W3203245760","https://openalex.org/W3211250490","https://openalex.org/W3215720729","https://openalex.org/W3216759837","https://openalex.org/W4200302647","https://openalex.org/W4210251751","https://openalex.org/W4220717373","https://openalex.org/W4308627565","https://openalex.org/W4310862819","https://openalex.org/W4313201790","https://openalex.org/W4382516701","https://openalex.org/W4384636150","https://openalex.org/W4387662324","https://openalex.org/W4390665506","https://openalex.org/W4390937897","https://openalex.org/W4391688210","https://openalex.org/W4392131866","https://openalex.org/W4392481289","https://openalex.org/W4393638533","https://openalex.org/W4394595135","https://openalex.org/W4396773505","https://openalex.org/W4400071971","https://openalex.org/W4401857407","https://openalex.org/W4403294825"],"related_works":[],"abstract_inverted_index":{"Addressing":[0],"the":[1,23,35,70,88,94,97,125,130,138,157],"persistent":[2],"challenge":[3],"of":[4,37,113],"learning":[5,14,18],"from":[6,137],"imbalanced":[7,44],"datasets":[8],"is":[9,26],"crucial":[10],"in":[11],"advancing":[12],"machine":[13,17],"applications.":[15],"Standard":[16],"algorithms":[19],"typically":[20],"assume":[21],"that":[22,108,124,161],"input":[24],"data":[25,40,71,90,112],"balanced,":[27],"and":[28,68,77,134,147,156,167],"they":[29],"often":[30],"struggle":[31],"to":[32,65,80,122],"effectively":[33],"learn":[34],"distribution":[36,133],"minority":[38,131],"class":[39,132,140],"when":[41],"dealing":[42],"with":[43],"data.":[45],"To":[46,92],"address":[47],"this,":[48],"our":[49],"study":[50],"designed":[51],"an":[52,100],"improved":[53],"Generative":[54],"Adversarial":[55],"Networks":[56],"(GANs)":[57],"model,":[58],"named":[59],"MDGAN,":[60],"for":[61],"tabular":[62],"sample":[63],"synthesis":[64],"augment":[66],"samples":[67,127],"balance":[69],"distribution.":[72,91],"MDGAN":[73,162],"employs":[74],"a":[75,117],"multi-generator":[76],"multi-discriminator":[78],"structure":[79],"capture":[81],"non-connected":[82],"subspace":[83],"manifolds,":[84],"thereby":[85],"better":[86,128],"fitting":[87],"complete":[89],"enhance":[93],"diversity":[95],"among":[96,103],"multiple":[98],"generators,":[99],"exclusive":[101],"loss":[102,119],"generators":[104],"was":[105,120],"designed,":[106],"ensuring":[107],"each":[109],"generator":[110],"produces":[111],"different":[114],"modalities.":[115],"Additionally,":[116],"contrastive":[118],"introduced":[121],"ensure":[123],"generated":[126],"fit":[129],"are":[135],"separated":[136],"majority":[139],"distribution,":[141],"preventing":[142],"blurred":[143],"classification":[144],"boundaries.":[145],"Qualitative":[146],"quantitative":[148],"tests":[149],"were":[150],"conducted":[151],"on":[152],"25":[153],"real":[154],"datasets,":[155],"experimental":[158],"results":[159],"indicate":[160],"outperforms":[163],"traditional":[164],"classical":[165],"models":[166],"current":[168],"advanced":[169],"oversampling":[170],"models.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-05-07T13:39:58.223016","created_date":"2025-10-10T00:00:00"}