{"id":"https://openalex.org/W4390284838","doi":"https://doi.org/10.1109/tsmc.2023.3335241","title":"BO-SMOTE: A Novel Bayesian-Optimization-Based Synthetic Minority Oversampling Technique","display_name":"BO-SMOTE: A Novel Bayesian-Optimization-Based Synthetic Minority Oversampling Technique","publication_year":2023,"publication_date":"2023-12-27","ids":{"openalex":"https://openalex.org/W4390284838","doi":"https://doi.org/10.1109/tsmc.2023.3335241"},"language":"en","primary_location":{"id":"doi:10.1109/tsmc.2023.3335241","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2023.3335241","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"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 Systems, Man, and Cybernetics: Systems","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/A5113082345","display_name":"Shen Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I4391767858","display_name":"State Key Laboratory of Synthetical Automation for Process Industries","ror":"https://ror.org/0380ng272","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391767858","https://openalex.org/I9224756"]},{"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":"Shen Yan","raw_affiliation_strings":["State Key Laboratory of Synthetical Automation for Process Industries and the College of Information Science and Engineering, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries and the College of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756","https://openalex.org/I4391767858"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102919922","display_name":"Ziyan Zhao","orcid":"https://orcid.org/0000-0002-5858-4489"},"institutions":[{"id":"https://openalex.org/I4391767858","display_name":"State Key Laboratory of Synthetical Automation for Process Industries","ror":"https://ror.org/0380ng272","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391767858","https://openalex.org/I9224756"]},{"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":false,"raw_author_name":"Ziyan Zhao","raw_affiliation_strings":["State Key Laboratory of Synthetical Automation for Process Industries and the College of Information Science and Engineering, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries and the College of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756","https://openalex.org/I4391767858"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101517221","display_name":"Shixin Liu","orcid":"https://orcid.org/0000-0002-3404-9297"},"institutions":[{"id":"https://openalex.org/I4391767858","display_name":"State Key Laboratory of Synthetical Automation for Process Industries","ror":"https://ror.org/0380ng272","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391767858","https://openalex.org/I9224756"]},{"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":false,"raw_author_name":"Shixin Liu","raw_affiliation_strings":["State Key Laboratory of Synthetical Automation for Process Industries and the College of Information Science and Engineering, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries and the College of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756","https://openalex.org/I4391767858"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081318069","display_name":"MengChu Zhou","orcid":"https://orcid.org/0000-0002-5408-8752"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]},{"id":"https://openalex.org/I75059550","display_name":"Zhejiang Gongshang University","ror":"https://ror.org/0569mkk41","country_code":"CN","type":"education","lineage":["https://openalex.org/I75059550"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Mengchu Zhou","raw_affiliation_strings":["School of Information and Electronic Engineering, Zhejiang Gongshang University, Hangzhou, China","Helen and John C. Hartmann the Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronic Engineering, Zhejiang Gongshang University, Hangzhou, China","institution_ids":["https://openalex.org/I75059550"]},{"raw_affiliation_string":"Helen and John C. Hartmann the Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5113082345"],"corresponding_institution_ids":["https://openalex.org/I4391767858","https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":5.1909,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.96499136,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"54","issue":"4","first_page":"2079","last_page":"2091"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T13429","display_name":"Electricity Theft Detection Techniques","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.977400004863739,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/oversampling","display_name":"Oversampling","score":0.9516042470932007},{"id":"https://openalex.org/keywords/randomness","display_name":"Randomness","score":0.7369036674499512},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.664376974105835},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5970218181610107},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.576184093952179},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5456065535545349},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.5229802131652832},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5136730074882507},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4723052978515625},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.45807644724845886},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.4460950195789337},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.42520755529403687},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3962029814720154},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38777703046798706},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33386266231536865},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2642216682434082},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.1779976785182953}],"concepts":[{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.9516042470932007},{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.7369036674499512},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.664376974105835},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5970218181610107},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.576184093952179},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5456065535545349},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.5229802131652832},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5136730074882507},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4723052978515625},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.45807644724845886},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.4460950195789337},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.42520755529403687},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3962029814720154},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38777703046798706},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33386266231536865},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2642216682434082},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.1779976785182953},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsmc.2023.3335241","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2023.3335241","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"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 Systems, Man, and Cybernetics: Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2592591841","display_name":null,"funder_award_id":"62073069","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3176671857","display_name":null,"funder_award_id":"2021YFB3301200","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G3858692165","display_name":null,"funder_award_id":"62203093","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G610315503","display_name":null,"funder_award_id":"XLYC2002041","funder_id":"https://openalex.org/F4320329895","funder_display_name":"Liaoning Revitalization Talents Program"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329895","display_name":"Liaoning Revitalization Talents Program","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":74,"referenced_works":["https://openalex.org/W123443654","https://openalex.org/W211765568","https://openalex.org/W1492095519","https://openalex.org/W1510052597","https://openalex.org/W1960182310","https://openalex.org/W1965337628","https://openalex.org/W1967127231","https://openalex.org/W1989249186","https://openalex.org/W1993220166","https://openalex.org/W1993336459","https://openalex.org/W1999318832","https://openalex.org/W2009754619","https://openalex.org/W2061481434","https://openalex.org/W2076272581","https://openalex.org/W2087189938","https://openalex.org/W2087240369","https://openalex.org/W2099201756","https://openalex.org/W2099454382","https://openalex.org/W2107138773","https://openalex.org/W2108114251","https://openalex.org/W2109509105","https://openalex.org/W2118581865","https://openalex.org/W2118978333","https://openalex.org/W2123969444","https://openalex.org/W2124710650","https://openalex.org/W2136816045","https://openalex.org/W2146713522","https://openalex.org/W2148143831","https://openalex.org/W2151356078","https://openalex.org/W2166566250","https://openalex.org/W2167789032","https://openalex.org/W2172165257","https://openalex.org/W2192203593","https://openalex.org/W2200953330","https://openalex.org/W2338318698","https://openalex.org/W2344304498","https://openalex.org/W2354826874","https://openalex.org/W2509669877","https://openalex.org/W2512389528","https://openalex.org/W2543431748","https://openalex.org/W2548109252","https://openalex.org/W2562319768","https://openalex.org/W2585510674","https://openalex.org/W2598548966","https://openalex.org/W2600610494","https://openalex.org/W2611252858","https://openalex.org/W2766742395","https://openalex.org/W2768552067","https://openalex.org/W2783151797","https://openalex.org/W2800788706","https://openalex.org/W2829536470","https://openalex.org/W2928048063","https://openalex.org/W2948219206","https://openalex.org/W2966679659","https://openalex.org/W2997591727","https://openalex.org/W3034578890","https://openalex.org/W3082260310","https://openalex.org/W3091787675","https://openalex.org/W3093212523","https://openalex.org/W3111875476","https://openalex.org/W3119363261","https://openalex.org/W3128474010","https://openalex.org/W3151089061","https://openalex.org/W3192988454","https://openalex.org/W4200122681","https://openalex.org/W4210854019","https://openalex.org/W4211049957","https://openalex.org/W4213128329","https://openalex.org/W4225407267","https://openalex.org/W4289761856","https://openalex.org/W6675200109","https://openalex.org/W6676576766","https://openalex.org/W6678911119","https://openalex.org/W6753146606"],"related_works":["https://openalex.org/W2766503024","https://openalex.org/W2781247653","https://openalex.org/W4206637278","https://openalex.org/W4386005305","https://openalex.org/W3082051559","https://openalex.org/W4401045170","https://openalex.org/W3172259201","https://openalex.org/W2903618681","https://openalex.org/W3184937791","https://openalex.org/W4401052546"],"abstract_inverted_index":{"An":[0],"oversampling":[1,25,240],"technique":[2],"balances":[3],"a":[4,15,54,83,176],"dataset":[5],"by":[6,51,101,170],"increasing":[7],"the":[8,39,48,64,92,118,121,130,136,141,147,150,164,171,185,194,206,210,213,217,231,245],"number":[9],"of":[10,42,67,75,143,174,208,212,220,248],"minority":[11,31,71,84,96,123,137],"samples.":[12,72,124,138],"It":[13],"is":[14,61,117,127,180],"common":[16],"and":[17,89],"effective":[18],"method":[19,233],"in":[20,29,146,200],"imbalanced":[21,93,227,249],"learning.":[22,250],"However,":[23],"most":[24],"methods":[26],"have":[27,35],"randomness":[28],"generating":[30],"samples,":[32],"which":[33],"would":[34],"negative":[36,218],"impacts":[37],"on":[38,205],"prediction":[40,49],"performance":[41,211],"subsequent":[43,68],"classifiers.":[44],"This":[45],"study":[46],"treats":[47],"made":[50],"classifiers":[52,69],"as":[53,82],"black-box":[55],"optimization":[56,59,77,103],"problem.":[57],"The":[58,73,95,125,197],"objective":[60],"to":[62,91,157,162,183],"improve":[63],"classification":[65],"accuracy":[66],"for":[70,110],"solution":[74],"this":[76,201],"problem":[78],"can":[79,87,153],"be":[80,88,154,168],"regarded":[81],"sample":[85,177],"that":[86,128,166,187,230],"added":[90],"dataset.":[94],"samples":[97,133,144,186,198],"are":[98,188,203],"iteratively":[99],"generated":[100,145,192,199],"Bayesian":[102],"(BO).":[104],"We":[105],"determine":[106],"two":[107,148],"valuable":[108],"intervals":[109],"each":[111],"1-D":[112],"continuous":[113],"variable":[114],"feature.":[115],"One":[116],"interval":[119],"with":[120,129],"densest":[122],"other":[126],"sparsest":[131],"majority":[132],"distributed":[134],"among":[135],"By":[139],"adjusting":[140],"proportion":[142],"areas,":[149],"presented":[151],"algorithm":[152],"flexibly":[155],"applied":[156],"different":[158],"datasets.":[159],"In":[160],"order":[161],"reduce":[163],"noise":[165],"may":[167],"caused":[169],"exploration":[172],"phase":[173],"BO,":[175],"selection":[178],"procedure":[179],"carried":[181],"out":[182],"eliminate":[184],"worse":[189],"than":[190,237],"those":[191],"at":[193],"previous":[195],"iteration.":[196],"way":[202],"based":[204],"principle":[207],"improving":[209],"classifier,":[214],"thus":[215,242],"avoiding":[216],"effects":[219],"randomness.":[221],"Experimental":[222],"results":[223,236],"via":[224],"twenty":[225],"open":[226],"datasets":[228],"show":[229],"proposed":[232],"obtains":[234],"better":[235],"existing":[238],"state-of-the-art":[239],"models,":[241],"well":[243],"advancing":[244],"important":[246],"field":[247]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":15}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
