{"id":"https://openalex.org/W4296910038","doi":"https://doi.org/10.1109/access.2022.3208715","title":"Machine Learning Model Generation With Copula-Based Synthetic Dataset for Local Differentially Private Numerical Data","display_name":"Machine Learning Model Generation With Copula-Based Synthetic Dataset for Local Differentially Private Numerical Data","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4296910038","doi":"https://doi.org/10.1109/access.2022.3208715"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3208715","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3208715","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09899428.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09899428.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045716284","display_name":"Yuichi Sei","orcid":"https://orcid.org/0000-0002-2552-6717"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]},{"id":"https://openalex.org/I4210086780","display_name":"Japan Science and Technology Agency","ror":"https://ror.org/00097mb19","country_code":"JP","type":"government","lineage":["https://openalex.org/I1319490839","https://openalex.org/I4210086780"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuichi Sei","raw_affiliation_strings":["Department of Informatics, Graduate School of Informatics and Engineering, The University of Electro-Communications, Chofu, Tokyo, Japan","JST, PRESTO, Kawaguchi, Saitama, Japan"],"raw_orcid":"https://orcid.org/0000-0002-2552-6717","affiliations":[{"raw_affiliation_string":"Department of Informatics, Graduate School of Informatics and Engineering, The University of Electro-Communications, Chofu, Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]},{"raw_affiliation_string":"JST, PRESTO, Kawaguchi, Saitama, Japan","institution_ids":["https://openalex.org/I4210086780"]}]},{"author_position":"middle","author":{"id":null,"display_name":"J. Andrew Onesimu","orcid":"https://orcid.org/0000-0003-3592-6543"},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"J. Andrew Onesimu","raw_affiliation_strings":["Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India"],"raw_orcid":"https://orcid.org/0000-0003-3592-6543","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013259601","display_name":"Akihiko Ohsuga","orcid":"https://orcid.org/0000-0001-6717-7028"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akihiko Ohsuga","raw_affiliation_strings":["Department of Informatics, Graduate School of Informatics and Engineering, The University of Electro-Communications, Chofu, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0001-6717-7028","affiliations":[{"raw_affiliation_string":"Department of Informatics, Graduate School of Informatics and Engineering, The University of Electro-Communications, Chofu, Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.1779,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.89066224,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"10","issue":null,"first_page":"101656","last_page":"101671"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","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/T10764","display_name":"Privacy-Preserving Technologies in Data","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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9847999811172485,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9789000153541565,"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/copula","display_name":"Copula (linguistics)","score":0.7326979041099548},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7085756063461304},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.6569875478744507},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5398122668266296},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5063985586166382},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.5014240741729736},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38608646392822266},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.24416899681091309},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12334200739860535}],"concepts":[{"id":"https://openalex.org/C17618745","wikidata":"https://www.wikidata.org/wiki/Q207509","display_name":"Copula (linguistics)","level":2,"score":0.7326979041099548},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7085756063461304},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.6569875478744507},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5398122668266296},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5063985586166382},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.5014240741729736},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38608646392822266},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.24416899681091309},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12334200739860535},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2022.3208715","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3208715","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09899428.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:irdb.nii.ac.jp:00931:0005725801","is_oa":true,"landing_page_url":"https://uec.repo.nii.ac.jp/records/10326","pdf_url":"https://uec.repo.nii.ac.jp/?action=repository_action_common_download&item_id=10326&item_no=1&attribute_id=22&file_no=1","source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access","raw_type":"journal article"},{"id":"pmh:oai:doaj.org/article:d0fec789fc9648849a7b6cbda9414959","is_oa":true,"landing_page_url":"https://doaj.org/article/d0fec789fc9648849a7b6cbda9414959","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 101656-101671 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3208715","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3208715","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09899428.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.5,"display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G1347699629","display_name":null,"funder_award_id":"JP21H03496","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G1348538837","display_name":"Privacy Protection Framework for a Ubiquitous Machine Learning Society","funder_award_id":"23K21695","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G359921329","display_name":"Web/IoT\u6a2a\u65ad\u7684\u30d7\u30e9\u30a4\u30d0\u30b7\u4fdd\u8b77\u30c7\u30fc\u30bf\u89e3\u6790\u57fa\u76e4","funder_award_id":"JPMJPR1934","funder_id":"https://openalex.org/F4320334789","funder_display_name":"Japan Science and Technology Agency"},{"id":"https://openalex.org/G5201537826","display_name":"Study of Atmosphere and Its Application to EdTech","funder_award_id":"19K12107","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G6494474583","display_name":"Social and physical sensor fusion mining infrastructure to understand behavioral intentions","funder_award_id":"18H03340","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G7058445323","display_name":"A Study on Locally Private Algorithms for Large-Scale Personal Data","funder_award_id":"19H04113","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G7774204308","display_name":"Research on autonomous cooperative self-adaptation mechanisms and formal verification of them","funder_award_id":"18H03229","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8517716559","display_name":"Flexible framework of privacy-preserving IoT data analysis","funder_award_id":"18K19835","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320334789","display_name":"Japan Science and Technology Agency","ror":"https://ror.org/00097mb19"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4296910038.pdf","grobid_xml":"https://content.openalex.org/works/W4296910038.grobid-xml"},"referenced_works_count":103,"referenced_works":["https://openalex.org/W1503398984","https://openalex.org/W1594031697","https://openalex.org/W1964166103","https://openalex.org/W1981029888","https://openalex.org/W1988950592","https://openalex.org/W2013587512","https://openalex.org/W2039663572","https://openalex.org/W2053637704","https://openalex.org/W2053801139","https://openalex.org/W2054191321","https://openalex.org/W2063978378","https://openalex.org/W2099122418","https://openalex.org/W2109642764","https://openalex.org/W2125055259","https://openalex.org/W2270330859","https://openalex.org/W2331697030","https://openalex.org/W2332073032","https://openalex.org/W2401583556","https://openalex.org/W2473418344","https://openalex.org/W2582328856","https://openalex.org/W2597425331","https://openalex.org/W2618574054","https://openalex.org/W2782864149","https://openalex.org/W2793685318","https://openalex.org/W2799331111","https://openalex.org/W2884766772","https://openalex.org/W2888588953","https://openalex.org/W2900935605","https://openalex.org/W2950321888","https://openalex.org/W2950943617","https://openalex.org/W2963038732","https://openalex.org/W2963693643","https://openalex.org/W2964116855","https://openalex.org/W2964881778","https://openalex.org/W2967204672","https://openalex.org/W2967889168","https://openalex.org/W2968213045","https://openalex.org/W2977797911","https://openalex.org/W2978172845","https://openalex.org/W2978348882","https://openalex.org/W2981195730","https://openalex.org/W2983509101","https://openalex.org/W2997422449","https://openalex.org/W2999456552","https://openalex.org/W3004158152","https://openalex.org/W3006101764","https://openalex.org/W3015535799","https://openalex.org/W3016632787","https://openalex.org/W3018026610","https://openalex.org/W3019109548","https://openalex.org/W3025903272","https://openalex.org/W3027749727","https://openalex.org/W3031648392","https://openalex.org/W3033250580","https://openalex.org/W3033686777","https://openalex.org/W3035161663","https://openalex.org/W3039234028","https://openalex.org/W3041809298","https://openalex.org/W3046518446","https://openalex.org/W3047327820","https://openalex.org/W3080895617","https://openalex.org/W3081876271","https://openalex.org/W3088349136","https://openalex.org/W3091870957","https://openalex.org/W3092945970","https://openalex.org/W3093068007","https://openalex.org/W3095595244","https://openalex.org/W3099845542","https://openalex.org/W3100779497","https://openalex.org/W3102834148","https://openalex.org/W3105797690","https://openalex.org/W3111259855","https://openalex.org/W3116386889","https://openalex.org/W3119464161","https://openalex.org/W3120740533","https://openalex.org/W3129519326","https://openalex.org/W3134824859","https://openalex.org/W3136573396","https://openalex.org/W3171292122","https://openalex.org/W3190219082","https://openalex.org/W3194459593","https://openalex.org/W3197295672","https://openalex.org/W4212883601","https://openalex.org/W4236137412","https://openalex.org/W4285133243","https://openalex.org/W4285722492","https://openalex.org/W4288359825","https://openalex.org/W4289293239","https://openalex.org/W4293193204","https://openalex.org/W4294092922","https://openalex.org/W6677855611","https://openalex.org/W6737985840","https://openalex.org/W6741867943","https://openalex.org/W6742396582","https://openalex.org/W6749577271","https://openalex.org/W6756281437","https://openalex.org/W6758745068","https://openalex.org/W6762194394","https://openalex.org/W6779561255","https://openalex.org/W6780036764","https://openalex.org/W6784683552","https://openalex.org/W6784729627","https://openalex.org/W6787376386"],"related_works":["https://openalex.org/W4254184784","https://openalex.org/W1502836838","https://openalex.org/W2351412012","https://openalex.org/W2117969153","https://openalex.org/W2066826592","https://openalex.org/W1967916041","https://openalex.org/W3109499659","https://openalex.org/W4382315317","https://openalex.org/W2966641257","https://openalex.org/W3186268266"],"abstract_inverted_index":{"With":[0],"the":[1,29,52,59,83,110,120,133,162,165,171],"development":[2],"of":[3,54,91,112,125,164],"IoT":[4],"technology,":[5],"personal":[6,36],"data":[7,15,37,48,60],"are":[8,49,103],"being":[9],"collected":[10],"in":[11],"many":[12],"places.":[13],"These":[14],"can":[16,33],"be":[17,26],"used":[18],"to":[19,28,69],"create":[20,191],"new":[21],"services,":[22],"but":[23,175],"consideration":[24],"must":[25],"given":[27],"individual\u2019s":[30],"privacy.":[31,44,117],"We":[32,80],"safely":[34],"collect":[35],"while":[38,108],"adding":[39],"noise":[40,113],"by":[41,58,115],"applying":[42,92],"differential":[43,116,200],"However,":[45],"because":[46],"such":[47,182,195],"very":[50],"noisy,":[51],"accuracy":[53],"machine":[55,74,86,179,192],"learning":[56,75,87,180,193],"trained":[57],"greatly":[61],"decreased.":[62],"In":[63,118],"this":[64],"study,":[65],"our":[66],"objective":[67],"is":[68],"build":[70],"a":[71,98,106,129,139],"highly":[72],"accurate":[73],"model":[76],"using":[77,105,156,199],"these":[78],"data.":[79,202],"focus":[81],"on":[82],"decision":[84,172],"tree":[85,173],"algorithm,":[88],"and,":[89],"instead":[90],"it":[93],"as":[94,183,196],"is,":[95],"we":[96],"use":[97],"preprocessing":[99],"technique":[100],"wherein":[101],"pseudodata":[102],"generated":[104],"copula":[107],"removing":[109],"effect":[111],"added":[114],"detail,":[119],"proposed":[121,166],"novel":[122],"protocol":[123],"consists":[124],"three":[126],"steps:":[127],"generating":[128,138,150],"covariance":[130],"matrix":[131],"from":[132,144],"differentially":[134,145],"private":[135,146],"numerical":[136,147,152],"data,":[137,148],"discrete":[140],"cumulative":[141],"distribution":[142],"function":[143],"and":[149,158],"copula-based":[151],"samples.":[153],"Simulation":[154],"results":[155],"synthetic":[157],"real":[159],"datasets":[160],"verify":[161],"utility":[163],"method":[167,188],"not":[168],"only":[169],"for":[170,177],"algorithm":[174],"also":[176],"other":[178],"algorithms":[181],"deep":[184],"neural":[185],"networks.":[186],"This":[187],"will":[189],"help":[190],"models,":[194],"recommendation":[197],"systems,":[198],"privacy":[201]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":4}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}
