{"id":"https://openalex.org/W2907349234","doi":"https://doi.org/10.1109/iecon.2018.8591109","title":"DOSS: Dual Over Sampling Strategy for Imbalanced Data Classification","display_name":"DOSS: Dual Over Sampling Strategy for Imbalanced Data Classification","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2907349234","doi":"https://doi.org/10.1109/iecon.2018.8591109","mag":"2907349234"},"language":"en","primary_location":{"id":"doi:10.1109/iecon.2018.8591109","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon.2018.8591109","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society","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/A5100411690","display_name":"Qiushi Wang","orcid":"https://orcid.org/0000-0001-7678-6941"},"institutions":[{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Qiushi Wang","raw_affiliation_strings":["Manufacturing Execution and Control Group, Singapore Institute of Manufacturing Technology(SIMTech), Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Manufacturing Execution and Control Group, Singapore Institute of Manufacturing Technology(SIMTech), Singapore","institution_ids":["https://openalex.org/I4210091207"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009271194","display_name":"Kee Jin Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Kee Jin Lee","raw_affiliation_strings":["Manufacturing Execution and Control Group, Singapore Institute of Manufacturing Technology(SIMTech), Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Manufacturing Execution and Control Group, Singapore Institute of Manufacturing Technology(SIMTech), Singapore","institution_ids":["https://openalex.org/I4210091207"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103262814","display_name":"Jihoon Hong","orcid":"https://orcid.org/0000-0002-2407-8107"},"institutions":[{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jihoon Hong","raw_affiliation_strings":["Manufacturing Execution and Control Group, Singapore Institute of Manufacturing Technology(SIMTech), Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Manufacturing Execution and Control Group, Singapore Institute of Manufacturing Technology(SIMTech), Singapore","institution_ids":["https://openalex.org/I4210091207"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210091207"],"apc_list":null,"apc_paid":null,"fwci":0.169,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.62786131,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"27","issue":null,"first_page":"5389","last_page":"5394"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9941999912261963,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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":0.9795300960540771},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6755079030990601},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.674984872341156},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6700130701065063},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6418265104293823},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6338421702384949},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4782794415950775},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.4423840641975403},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.41980427503585815},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34746772050857544},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.10757282376289368}],"concepts":[{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.9795300960540771},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6755079030990601},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.674984872341156},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6700130701065063},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6418265104293823},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6338421702384949},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4782794415950775},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.4423840641975403},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.41980427503585815},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34746772050857544},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.10757282376289368},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"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},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iecon.2018.8591109","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon.2018.8591109","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334747","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1993220166","https://openalex.org/W2030832258","https://openalex.org/W2099471712","https://openalex.org/W2118978333","https://openalex.org/W2148143831","https://openalex.org/W2273614765","https://openalex.org/W2295598076","https://openalex.org/W2562319768","https://openalex.org/W2756182389","https://openalex.org/W2768348081","https://openalex.org/W3102476541","https://openalex.org/W4320013936","https://openalex.org/W6745609711"],"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/W4386214543","https://openalex.org/W1969988626","https://openalex.org/W2141301039","https://openalex.org/W3173198409","https://openalex.org/W2152863486"],"abstract_inverted_index":{"Imbalanced":[0],"datasets":[1,182],"are":[2,45,81,113,162,171],"often":[3],"encountered":[4],"in":[5,49],"process":[6],"monitoring,":[7],"where":[8,205],"the":[9,20,29,33,38,57,63,67,74,83,108,117,130,141,154,174,184,197,206],"data":[10,21,118],"reflecting":[11,22],"abnormal":[12],"events":[13],"like":[14],"machine":[15,42,204],"failures":[16],"is":[17,27,35,121,138,147,157,192],"less":[18],"than":[19],"normal":[23],"events.":[24],"The":[25,144,176],"former":[26],"called":[28],"minority":[30,68,131,155],"class":[31,69,85,156],"and":[32,169],"later":[34],"referred":[36],"as":[37,89,140,173],"majority":[39,84,109],"class.":[40],"Classical":[41],"learning":[43],"algorithms":[44],"still":[46],"facing":[47],"challenges":[48],"solving":[50],"this":[51,92],"problem.":[52],"In":[53,91],"order":[54],"to":[55,101,116,195],"improve":[56],"classification":[58],"accuracy,":[59],"oversampling":[60,98,142],"techniques":[61],"rebalance":[62],"dataset":[64],"by":[65,123],"supplying":[66],"with":[70,149,164],"synthetic":[71,111],"samples.":[72],"However,":[73],"latent":[75],"sample":[76],"spaces":[77],"of":[78,187,200,208],"both":[79,105,160],"classes":[80,161],"broad,":[82],"might":[86],"be":[87],"under-represented":[88],"well.":[90],"paper,":[93],"we":[94],"propose":[95],"a":[96,211],"dual":[97],"strategy":[99,146],"(DOSS)":[100],"generate":[102],"samples":[103,112],"for":[104],"classes.":[106],"For":[107,129],"class,":[110,132],"generated":[114],"according":[115],"distribution,":[119],"which":[120],"approximated":[122],"conditional":[124],"Generative":[125],"Adversarial":[126],"Network":[127],"(cGAN).":[128],"Synthetic":[133],"Minority":[134],"Over-sampling":[135],"Technique":[136],"(SMOTE)":[137],"applied":[139,194],"method.":[143],"proposed":[145,189],"compared":[148],"others":[150],"that":[151],"either":[152],"only":[153],"oversampled":[158,163],"or":[159],"different":[165],"strategies.":[166],"Recall,":[167],"G-mean":[168],"F-measure":[170],"used":[172],"metrics.":[175],"experimental":[177],"results":[178],"on":[179],"12":[180],"benchmark":[181],"show":[183],"improved":[185],"performance":[186],"our":[188],"strategy.":[190],"DOSS":[191,209],"further":[193],"detect":[196],"faulty":[198],"stages":[199],"an":[201],"injection":[202],"moulding":[203],"prediction":[207],"achieves":[210],"better":[212],"accuracy.":[213]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}