{"id":"https://openalex.org/W2922054794","doi":"https://doi.org/10.1109/tkde.2019.2905559","title":"Model-Based Synthetic Sampling for Imbalanced Data","display_name":"Model-Based Synthetic Sampling for Imbalanced Data","publication_year":2019,"publication_date":"2019-03-18","ids":{"openalex":"https://openalex.org/W2922054794","doi":"https://doi.org/10.1109/tkde.2019.2905559","mag":"2922054794"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2019.2905559","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2019.2905559","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/A5031322893","display_name":"Chien\u2010Liang Liu","orcid":"https://orcid.org/0000-0002-2724-7199"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chien-Liang Liu","raw_affiliation_strings":["Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-2724-7199","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056778267","display_name":"Po-Yen Hsieh","orcid":null},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Po-Yen Hsieh","raw_affiliation_strings":["Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I148366613"],"apc_list":null,"apc_paid":null,"fwci":5.2134,"has_fulltext":false,"cited_by_count":89,"citation_normalized_percentile":{"value":0.96130621,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"32","issue":"8","first_page":"1543","last_page":"1556"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9821000099182129,"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":0.9807000160217285,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8313785791397095},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6239619851112366},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5864095091819763},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5778073668479919},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.5246472954750061},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4949166178703308},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4921221137046814},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.46168604493141174},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4445292055606842}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8313785791397095},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6239619851112366},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5864095091819763},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5778073668479919},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.5246472954750061},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4949166178703308},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4921221137046814},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.46168604493141174},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4445292055606842},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2019.2905559","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2019.2905559","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/G4958146032","display_name":"Ideepcare: Intelligent Deep-Level Healthcare Using Deep Machine Learning and Big Data Analytics Techniques( III )","funder_award_id":"MOST107-2218-E009-005","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"},{"id":"https://openalex.org/G6970405991","display_name":"Early Prediction System for Postoperative Acute Rejection of Liver Transplant Patient","funder_award_id":"MOST107-2221-E009-109-MY2","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"},{"id":"https://openalex.org/F4320337253","display_name":"Instituto de Ciencias del Mar y Limnolog\u00eda, Universidad Nacional Aut\u00f3noma de M\u00e9xico","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W85350352","https://openalex.org/W795388544","https://openalex.org/W1496056137","https://openalex.org/W1563938718","https://openalex.org/W1673310716","https://openalex.org/W1842879116","https://openalex.org/W1965833531","https://openalex.org/W1988790447","https://openalex.org/W1993220166","https://openalex.org/W1996523702","https://openalex.org/W2011376672","https://openalex.org/W2015452969","https://openalex.org/W2015681982","https://openalex.org/W2023299139","https://openalex.org/W2032210760","https://openalex.org/W2040010062","https://openalex.org/W2065330407","https://openalex.org/W2067802406","https://openalex.org/W2070808135","https://openalex.org/W2083780116","https://openalex.org/W2099435377","https://openalex.org/W2099454382","https://openalex.org/W2104167780","https://openalex.org/W2104933073","https://openalex.org/W2118978333","https://openalex.org/W2128965734","https://openalex.org/W2131904035","https://openalex.org/W2132791018","https://openalex.org/W2145073242","https://openalex.org/W2148143831","https://openalex.org/W2172073485","https://openalex.org/W2187089797","https://openalex.org/W2338318698","https://openalex.org/W2440599146","https://openalex.org/W2520599539","https://openalex.org/W2532073801","https://openalex.org/W2596340169","https://openalex.org/W2798869704","https://openalex.org/W2912934387","https://openalex.org/W2964050365","https://openalex.org/W4212883601","https://openalex.org/W4230683138","https://openalex.org/W4239510810","https://openalex.org/W4244036394","https://openalex.org/W4244952642","https://openalex.org/W4248437541","https://openalex.org/W4251708881","https://openalex.org/W6603460400","https://openalex.org/W6637131181","https://openalex.org/W6675634716","https://openalex.org/W6679539681","https://openalex.org/W6681651645","https://openalex.org/W6750348571"],"related_works":["https://openalex.org/W2140798747","https://openalex.org/W2948169060","https://openalex.org/W2730112582","https://openalex.org/W2110696645","https://openalex.org/W2358580169","https://openalex.org/W2111347279","https://openalex.org/W3109499659","https://openalex.org/W4382315317","https://openalex.org/W2966641257","https://openalex.org/W4399530423"],"abstract_inverted_index":{"Imbalanced":[0],"data":[1,21,132,138,188],"is":[2,42,67,118,162],"characterized":[3],"by":[4],"the":[5,39,45,115,125,135,148,159,177],"severe":[6],"difference":[7],"in":[8,20,78,99,134],"observation":[9],"frequency":[10],"between":[11,127],"classes":[12],"and":[13,104,129,146,174],"has":[14],"received":[15],"a":[16,86],"lot":[17],"of":[18,50,137,176],"attention":[19],"mining":[22],"research.":[23],"The":[24,111,154],"prediction":[25],"performances":[26],"usually":[27],"deteriorate":[28],"as":[29,35],"classifiers":[30,37],"learn":[31],"from":[32],"imbalanced":[33],"data,":[34],"most":[36,79],"assume":[38],"class":[40],"distribution":[41],"balanced":[43],"or":[44],"costs":[46],"for":[47],"different":[48],"types":[49],"classification":[51],"errors":[52],"are":[53],"equal.":[54],"Although":[55],"several":[56],"methods":[57,73],"have":[58],"been":[59],"devised":[60],"to":[61,70,74,94,107,119,123,130,180],"deal":[62],"with":[63,96,151],"imbalance":[64,97],"problems,":[65,98],"it":[66,184],"still":[68],"difficult":[69],"generalize":[71],"those":[72],"achieve":[75],"stable":[76],"improvement":[77],"cases.":[80],"In":[81],"this":[82],"study,":[83],"we":[84,101],"propose":[85],"novel":[87],"framework":[88],"called":[89],"model-based":[90],"synthetic":[91,109],"sampling":[92,105],"(MBS)":[93],"cope":[95],"which":[100],"integrate":[102],"modeling":[103],"techniques":[106],"generate":[108,186],"data.":[110],"key":[112],"idea":[113],"behind":[114],"proposed":[116,149,160,178],"method":[117,150,161,179],"use":[120],"regression":[121],"models":[122],"capture":[124],"relationship":[126],"features":[128],"consider":[131],"diversity":[133],"process":[136],"generation.":[139],"We":[140,169],"conduct":[141],"experiments":[142],"on":[143],"13":[144],"datasets":[145],"compare":[147],"10":[152],"methods.":[153],"experimental":[155],"results":[156],"indicate":[157],"that":[158],"not":[163],"only":[164],"comparative":[165],"but":[166],"also":[167,170],"stable.":[168],"provide":[171],"detailed":[172],"investigations":[173],"visualizations":[175],"empirically":[181],"demonstrate":[182],"why":[183],"could":[185],"good":[187],"samples.":[189]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}