{"id":"https://openalex.org/W4309969736","doi":"https://doi.org/10.1109/ictc55196.2022.9952762","title":"Generative Data Augmentation via Wasserstein Autoencoder for Text Classification","display_name":"Generative Data Augmentation via Wasserstein Autoencoder for Text Classification","publication_year":2022,"publication_date":"2022-10-19","ids":{"openalex":"https://openalex.org/W4309969736","doi":"https://doi.org/10.1109/ictc55196.2022.9952762"},"language":"en","primary_location":{"id":"doi:10.1109/ictc55196.2022.9952762","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc55196.2022.9952762","pdf_url":null,"source":{"id":"https://openalex.org/S4363607740","display_name":"2022 13th International Conference on Information and Communication Technology Convergence (ICTC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 13th International Conference on Information and Communication Technology Convergence (ICTC)","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/A5028883212","display_name":"Kyohoon Jin","orcid":"https://orcid.org/0000-0002-7824-3577"},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Kyohoon Jin","raw_affiliation_strings":["Chung-Ang University,Department of Image Science and Arts,Seoul,South Korea","Department of Image Science and Arts, Chung-Ang University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Chung-Ang University,Department of Image Science and Arts,Seoul,South Korea","institution_ids":["https://openalex.org/I67900169"]},{"raw_affiliation_string":"Department of Image Science and Arts, Chung-Ang University, Seoul, South Korea","institution_ids":["https://openalex.org/I67900169"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100366257","display_name":"Junho Lee","orcid":"https://orcid.org/0009-0004-1440-9322"},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junho Lee","raw_affiliation_strings":["Chung-Ang University,Department of Artificial Intelligence,Seoul,South Korea","Department of Artificial Intelligence, Chung-Ang University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Chung-Ang University,Department of Artificial Intelligence,Seoul,South Korea","institution_ids":["https://openalex.org/I67900169"]},{"raw_affiliation_string":"Department of Artificial Intelligence, Chung-Ang University, Seoul, South Korea","institution_ids":["https://openalex.org/I67900169"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101772444","display_name":"Juhwan Choi","orcid":"https://orcid.org/0000-0003-0657-581X"},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Juhwan Choi","raw_affiliation_strings":["School of Electrical and Electronics Engineering, Chung-Ang University,Seoul,South Korea","School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronics Engineering, Chung-Ang University,Seoul,South Korea","institution_ids":["https://openalex.org/I67900169"]},{"raw_affiliation_string":"School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, South Korea","institution_ids":["https://openalex.org/I67900169"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013982522","display_name":"Soojin Jang","orcid":"https://orcid.org/0000-0002-2719-7646"},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Soojin Jang","raw_affiliation_strings":["Chung-Ang University,Department of Image Science and Arts,Seoul,South Korea","Department of Image Science and Arts, Chung-Ang University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Chung-Ang University,Department of Image Science and Arts,Seoul,South Korea","institution_ids":["https://openalex.org/I67900169"]},{"raw_affiliation_string":"Department of Image Science and Arts, Chung-Ang University, Seoul, South Korea","institution_ids":["https://openalex.org/I67900169"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016930939","display_name":"Youngbin Kim","orcid":"https://orcid.org/0000-0002-2114-0120"},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youngbin Kim","raw_affiliation_strings":["Chung-Ang University,Department of Image Science and Arts,Seoul,South Korea","Department of Image Science and Arts, Chung-Ang University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Chung-Ang University,Department of Image Science and Arts,Seoul,South Korea","institution_ids":["https://openalex.org/I67900169"]},{"raw_affiliation_string":"Department of Image Science and Arts, Chung-Ang University, Seoul, South Korea","institution_ids":["https://openalex.org/I67900169"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5028883212"],"corresponding_institution_ids":["https://openalex.org/I67900169"],"apc_list":null,"apc_paid":null,"fwci":0.1041,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.30760114,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"21","issue":null,"first_page":"603","last_page":"607"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10028","display_name":"Topic Modeling","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9980000257492065,"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.9890000224113464,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.9487070441246033},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.8024424910545349},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.7835742235183716},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.7311393618583679},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6929072737693787},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6927619576454163},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6115140318870544},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.5357235074043274},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4553828537464142},{"id":"https://openalex.org/keywords/latent-variable-model","display_name":"Latent variable model","score":0.4467259347438812},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4345320463180542},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41444748640060425},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3313635587692261},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2432839274406433},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1386413872241974}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9487070441246033},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.8024424910545349},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.7835742235183716},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.7311393618583679},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6929072737693787},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6927619576454163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6115140318870544},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.5357235074043274},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4553828537464142},{"id":"https://openalex.org/C65965080","wikidata":"https://www.wikidata.org/wiki/Q1806885","display_name":"Latent variable model","level":3,"score":0.4467259347438812},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4345320463180542},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41444748640060425},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3313635587692261},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2432839274406433},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1386413872241974},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ictc55196.2022.9952762","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc55196.2022.9952762","pdf_url":null,"source":{"id":"https://openalex.org/S4363607740","display_name":"2022 13th International Conference on Information and Communication Technology Convergence (ICTC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 13th International Conference on Information and Communication Technology Convergence (ICTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.75}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1552847225","https://openalex.org/W1832693441","https://openalex.org/W2085750684","https://openalex.org/W2113459411","https://openalex.org/W2251939518","https://openalex.org/W2407776548","https://openalex.org/W2767899794","https://openalex.org/W2790480741","https://openalex.org/W2896457183","https://openalex.org/W2905266130","https://openalex.org/W2910135751","https://openalex.org/W2944931850","https://openalex.org/W2946385697","https://openalex.org/W2951278869","https://openalex.org/W2951561177","https://openalex.org/W2954996726","https://openalex.org/W2963746531","https://openalex.org/W2966574105","https://openalex.org/W2971296908","https://openalex.org/W2979826702","https://openalex.org/W2986068180","https://openalex.org/W2992308087","https://openalex.org/W2998184481","https://openalex.org/W3010293452","https://openalex.org/W3034999214","https://openalex.org/W3100742171","https://openalex.org/W3105190746","https://openalex.org/W3152268000","https://openalex.org/W3157152805","https://openalex.org/W3176198948","https://openalex.org/W4287661386","https://openalex.org/W4288089799","https://openalex.org/W4288631803","https://openalex.org/W4300833946","https://openalex.org/W4385245566","https://openalex.org/W6676984168","https://openalex.org/W6688325169","https://openalex.org/W6691459498","https://openalex.org/W6713582272","https://openalex.org/W6739901393","https://openalex.org/W6745535286","https://openalex.org/W6746141323","https://openalex.org/W6755207826","https://openalex.org/W6757883768","https://openalex.org/W6758151150","https://openalex.org/W6760184523","https://openalex.org/W6762880976","https://openalex.org/W6766364717","https://openalex.org/W6769627184","https://openalex.org/W6774569510","https://openalex.org/W6782894144","https://openalex.org/W6793585041","https://openalex.org/W6794455618"],"related_works":["https://openalex.org/W2988134182","https://openalex.org/W2461917396","https://openalex.org/W2037497866","https://openalex.org/W4243467573","https://openalex.org/W4309969736","https://openalex.org/W4394785709","https://openalex.org/W2770818364","https://openalex.org/W2616125534","https://openalex.org/W2963987720","https://openalex.org/W2146310005"],"abstract_inverted_index":{"Generative":[0],"latent":[1,14,33],"variable":[2,15],"models":[3,16],"are":[4],"commonly":[5],"used":[6,83],"in":[7,89,98],"text":[8],"generation":[9],"and":[10,93,101,117],"augmentation.":[11],"However":[12],"generative":[13,91],"such":[17],"as":[18],"the":[19,44,55,69,75,90,94,99,105,110,119],"variational":[20],"autoencoder(VAE)":[21],"experience":[22],"a":[23,30,63,86],"posterior":[24,87],"collapse":[25,88],"problem":[26],"ignoring":[27],"learning":[28],"for":[29],"subset":[31],"of":[32],"variables":[34],"during":[35],"training.":[36],"In":[37,58],"particular,":[38],"this":[39,59],"phenomenon":[40],"frequently":[41],"occurs":[42],"when":[43],"VAE":[45],"is":[46],"applied":[47],"to":[48,84,103],"natural":[49],"language":[50,71],"processing,":[51],"which":[52],"may":[53],"degrade":[54],"reconstruction":[56],"performance.":[57,107],"paper,":[60],"we":[61],"propose":[62],"data":[64],"augmentation":[65,106,120],"method":[66,112],"based":[67],"on":[68,113],"pre-trained":[70],"model":[72],"(PLM)":[73],"using":[74],"Wasserstein":[76],"autoencoder":[77],"(WAE)":[78],"structure.":[79],"The":[80],"WAE":[81],"was":[82,96],"prevent":[85],"model,":[92],"PLM":[95],"placed":[97],"encoder":[100],"decoder":[102],"improve":[104],"We":[108],"evaluated":[109],"proposed":[111],"seven":[114],"benchmark":[115],"datasets":[116],"proved":[118],"effect.":[121]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}