{"id":"https://openalex.org/W2975288815","doi":"https://doi.org/10.1109/iccse.2019.8845453","title":"A Research on Generative Adversarial Networks Applied to Text Generation","display_name":"A Research on Generative Adversarial Networks Applied to Text Generation","publication_year":2019,"publication_date":"2019-08-01","ids":{"openalex":"https://openalex.org/W2975288815","doi":"https://doi.org/10.1109/iccse.2019.8845453","mag":"2975288815"},"language":"en","primary_location":{"id":"doi:10.1109/iccse.2019.8845453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccse.2019.8845453","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 14th International Conference on Computer Science &amp; Education (ICCSE)","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/A5100460297","display_name":"Chao Zhang","orcid":"https://orcid.org/0009-0007-2579-8783"},"institutions":[{"id":"https://openalex.org/I74525822","display_name":"Hubei University of Technology","ror":"https://ror.org/02d3fj342","country_code":"CN","type":"education","lineage":["https://openalex.org/I74525822"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chao Zhang","raw_affiliation_strings":["School of Computer Science, Hubei University of Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Hubei University of Technology, Wuhan, China","institution_ids":["https://openalex.org/I74525822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100551966","display_name":"Caiquan Xiong","orcid":null},"institutions":[{"id":"https://openalex.org/I74525822","display_name":"Hubei University of Technology","ror":"https://ror.org/02d3fj342","country_code":"CN","type":"education","lineage":["https://openalex.org/I74525822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Caiquan Xiong","raw_affiliation_strings":["School of Computer Science, Hubei University of Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Hubei University of Technology, Wuhan, China","institution_ids":["https://openalex.org/I74525822"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100608320","display_name":"Lingyun Wang","orcid":"https://orcid.org/0000-0002-2522-5439"},"institutions":[{"id":"https://openalex.org/I74525822","display_name":"Hubei University of Technology","ror":"https://ror.org/02d3fj342","country_code":"CN","type":"education","lineage":["https://openalex.org/I74525822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingyun Wang","raw_affiliation_strings":["School of Computer Science, Hubei University of Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Hubei University of Technology, Wuhan, China","institution_ids":["https://openalex.org/I74525822"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100460297"],"corresponding_institution_ids":["https://openalex.org/I74525822"],"apc_list":null,"apc_paid":null,"fwci":1.0122,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.8093732,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"913","last_page":"917"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10028","display_name":"Topic Modeling","score":0.9936000108718872,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/perplexity","display_name":"Perplexity","score":0.8831996917724609},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8459378480911255},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.7123087644577026},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6660979390144348},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6126453280448914},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.5744155049324036},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.5359519124031067},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5027670860290527},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5020568370819092},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.48778682947158813},{"id":"https://openalex.org/keywords/text-generation","display_name":"Text generation","score":0.469779908657074},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.4656551480293274},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4493466317653656},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43649184703826904},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42765581607818604},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4273150563240051},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.41141313314437866}],"concepts":[{"id":"https://openalex.org/C100279451","wikidata":"https://www.wikidata.org/wiki/Q372193","display_name":"Perplexity","level":3,"score":0.8831996917724609},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8459378480911255},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.7123087644577026},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6660979390144348},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6126453280448914},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5744155049324036},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.5359519124031067},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5027670860290527},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5020568370819092},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.48778682947158813},{"id":"https://openalex.org/C2985684807","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Text generation","level":2,"score":0.469779908657074},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.4656551480293274},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4493466317653656},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43649184703826904},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42765581607818604},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4273150563240051},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.41141313314437866},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccse.2019.8845453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccse.2019.8845453","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 14th International Conference on Computer Science &amp; Education (ICCSE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7599999904632568,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W648786980","https://openalex.org/W1832693441","https://openalex.org/W2155027007","https://openalex.org/W2174424190","https://openalex.org/W2405756170","https://openalex.org/W2547875792","https://openalex.org/W2581637843","https://openalex.org/W2592298275","https://openalex.org/W2593383075","https://openalex.org/W2602076750","https://openalex.org/W2949999304","https://openalex.org/W2962879692","https://openalex.org/W2964028737","https://openalex.org/W2977240061","https://openalex.org/W3136591341","https://openalex.org/W4295521014","https://openalex.org/W6621543089","https://openalex.org/W6683204974","https://openalex.org/W6713645886","https://openalex.org/W6729448088","https://openalex.org/W6734351891","https://openalex.org/W6734400285","https://openalex.org/W6735799286","https://openalex.org/W6735913928","https://openalex.org/W6739073796"],"related_works":["https://openalex.org/W2169518243","https://openalex.org/W2252095989","https://openalex.org/W4322096525","https://openalex.org/W2551914602","https://openalex.org/W4281893144","https://openalex.org/W4287323699","https://openalex.org/W2105076537","https://openalex.org/W2084531783","https://openalex.org/W2902731467","https://openalex.org/W2787311093"],"abstract_inverted_index":{"Using":[0],"deep":[1],"learning":[2,98],"methods":[3],"to":[4,101,123],"generate":[5],"text,":[6],"a":[7,26,41],"sequence-to-sequence":[8],"model":[9,43,70,104,137],"is":[10,17,40],"typically":[11],"used.":[12],"This":[13,65,152],"kind":[14],"of":[15,81,120,127],"models":[16,146],"very":[18],"effective":[19],"in":[20,48,56,139,156],"dealing":[21],"with":[22],"tasks":[23],"that":[24,44,134],"have":[25],"strong":[27],"correspondence":[28],"between":[29],"input":[30],"and":[31,59,94,110,117],"output,":[32],"such":[33,62],"as":[34,63,92],"machine":[35],"translation.":[36],"Generative":[37],"Adversarial":[38],"Networks(GAN)":[39],"generation":[42],"has":[45,52],"been":[46],"proposed":[47,138],"recent":[49],"years,":[50],"which":[51],"achieved":[53],"good":[54],"results":[55,132],"generating":[57],"continuous":[58],"divisible":[60],"data":[61],"images.":[64],"paper":[66,141],"proposes":[67],"an":[68],"improved":[69,136],"based":[71],"on":[72,147],"GAN,":[73],"specifically":[74],"using":[75,95],"the":[76,82,96,103,112,114,118,125,128,135],"transformer":[77],"network":[78],"structure":[79],"instead":[80],"original":[83],"general":[84],"Convolutional":[85],"Neural":[86,90],"Network":[87],"or":[88],"Recurrent":[89],"Networks":[91],"generator,":[93],"reinforcement":[97],"algorithm":[99],"Actor-Critic":[100],"improve":[102],"training":[105],"method.":[106],"By":[107],"comparing":[108],"experiments,":[109],"selecting":[111],"perplexity,":[113],"BLEU":[115],"score,":[116],"percentages":[119],"unique":[121],"n-gram":[122],"evaluate":[124],"quality":[126],"generated":[129],"sentences.":[130],"The":[131],"show":[133],"this":[140],"perform":[142],"better":[143],"than":[144],"comparative":[145],"above":[148],"three":[149],"evaluation":[150],"indexes.":[151],"verifies":[153],"its":[154],"effectiveness":[155],"text":[157],"generation.":[158]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
