{"id":"https://openalex.org/W4391096313","doi":"https://doi.org/10.1109/bigdata59044.2023.10386610","title":"An Augmentation-agnostic Semantic Preserving Technique for Data Generation","display_name":"An Augmentation-agnostic Semantic Preserving Technique for Data Generation","publication_year":2023,"publication_date":"2023-12-15","ids":{"openalex":"https://openalex.org/W4391096313","doi":"https://doi.org/10.1109/bigdata59044.2023.10386610"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata59044.2023.10386610","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata59044.2023.10386610","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Big Data (BigData)","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/A5100952349","display_name":"Jang\u2010Ho Choi","orcid":"https://orcid.org/0000-0002-9280-051X"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jang-Ho Choi","raw_affiliation_strings":["Intelligence Information Research Division Electronics and Telecommunications Research Institute,Daejeon,Republic of Korea","Intelligence Information Research Division Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligence Information Research Division Electronics and Telecommunications Research Institute,Daejeon,Republic of Korea","institution_ids":["https://openalex.org/I142401562"]},{"raw_affiliation_string":"Intelligence Information Research Division Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062211029","display_name":"Moonyoung Chung","orcid":null},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Moonyoung Chung","raw_affiliation_strings":["Intelligence Information Research Division Electronics and Telecommunications Research Institute,Daejeon,Republic of Korea","Intelligence Information Research Division Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligence Information Research Division Electronics and Telecommunications Research Institute,Daejeon,Republic of Korea","institution_ids":["https://openalex.org/I142401562"]},{"raw_affiliation_string":"Intelligence Information Research Division Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090139135","display_name":"Ji-Yong Kim","orcid":"https://orcid.org/0000-0002-2584-7123"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jiyong Kim","raw_affiliation_strings":["Intelligence Information Research Division Electronics and Telecommunications Research Institute,Daejeon,Republic of Korea","Intelligence Information Research Division Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligence Information Research Division Electronics and Telecommunications Research Institute,Daejeon,Republic of Korea","institution_ids":["https://openalex.org/I142401562"]},{"raw_affiliation_string":"Intelligence Information Research Division Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1848,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.48180017,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"6119","last_page":"6121"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9872999787330627,"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/computer-science","display_name":"Computer science","score":0.8234779238700867},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.6898637413978577},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.5699403285980225},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.5045706033706665},{"id":"https://openalex.org/keywords/external-data-representation","display_name":"External Data Representation","score":0.4925873875617981},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.4821302890777588},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.45490890741348267},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4481915831565857},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4370363652706146},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.41754698753356934},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4167298972606659},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.35970455408096313},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.09432822465896606}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8234779238700867},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.6898637413978577},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.5699403285980225},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.5045706033706665},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.4925873875617981},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.4821302890777588},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.45490890741348267},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4481915831565857},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4370363652706146},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.41754698753356934},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4167298972606659},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.35970455408096313},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.09432822465896606},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata59044.2023.10386610","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata59044.2023.10386610","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2620664872","https://openalex.org/W3101667008","https://openalex.org/W3157358876","https://openalex.org/W3190152617","https://openalex.org/W4286203191","https://openalex.org/W4382239668","https://openalex.org/W6908812986"],"related_works":["https://openalex.org/W4313443006","https://openalex.org/W2945374968","https://openalex.org/W4293777179","https://openalex.org/W4385452045","https://openalex.org/W2164070813","https://openalex.org/W2135608140","https://openalex.org/W2895525995","https://openalex.org/W2332512904","https://openalex.org/W4224231624","https://openalex.org/W2319626700"],"abstract_inverted_index":{"Data":[0],"generation":[1],"is":[2,36],"becoming":[3],"an":[4],"increasingly":[5],"important":[6],"issue":[7],"in":[8,44,57],"the":[9,16,23,86,89,99],"field":[10],"of":[11,19,88,101],"machine":[12],"learning":[13],"due":[14],"to":[15],"high":[17,34],"cost":[18],"data":[20,32,46,60],"collection":[21],"and":[22,68],"privacy":[24],"concerns":[25],"associated":[26],"with":[27,33],"raw":[28],"data.":[29,91],"Generating":[30],"new":[31],"fidelity":[35,87],"extremely":[37],"challenging":[38],"because":[39],"even":[40],"a":[41,78],"minor":[42],"perturbation":[43],"high-dimensional":[45],"may":[47],"alter":[48],"its":[49],"semantic":[50],"meaning.":[51],"The":[52],"challenge":[53],"becomes":[54],"particularly":[55],"acute":[56],"multivariate":[58],"time-series":[59,102],"as":[61],"it":[62],"often":[63],"exhibits":[64],"human-imperceptible":[65],"temporal":[66],"patterns":[67],"lacks":[69],"standard":[70],"representation.":[71],"To":[72],"address":[73],"this":[74],"issue,":[75],"we":[76],"propose":[77],"straightforward":[79],"yet":[80],"effective":[81],"technique":[82,97],"that":[83,95],"helps":[84],"preserve":[85],"original":[90],"Experimental":[92],"results":[93],"demonstrate":[94],"our":[96],"enhances":[98],"performance":[100],"forecasting":[103],"model.":[104]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
