{"id":"https://openalex.org/W3093130373","doi":"https://doi.org/10.3233/jifs-201370","title":"Imbalanced sentiment classification based on sequence generative adversarial nets","display_name":"Imbalanced sentiment classification based on sequence generative adversarial nets","publication_year":2020,"publication_date":"2020-08-27","ids":{"openalex":"https://openalex.org/W3093130373","doi":"https://doi.org/10.3233/jifs-201370","mag":"3093130373"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-201370","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-201370","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems","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/A5048128949","display_name":"Chuantao Wang","orcid":"https://orcid.org/0000-0002-4025-094X"},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]},{"id":"https://openalex.org/I4210118977","display_name":"Shanghai Tunnel Engineering Rail Transit Design & Research Institute","ror":"https://ror.org/02zznv955","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118977"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuantao Wang","raw_affiliation_strings":["Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles, Beijing, China","School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles, Beijing, China","institution_ids":["https://openalex.org/I4210118977"]},{"raw_affiliation_string":"School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China","institution_ids":["https://openalex.org/I62853816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002398665","display_name":"Yang Xuexin","orcid":"https://orcid.org/0000-0001-7873-5742"},"institutions":[{"id":"https://openalex.org/I4210118977","display_name":"Shanghai Tunnel Engineering Rail Transit Design & Research Institute","ror":"https://ror.org/02zznv955","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118977"]},{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuexin Yang","raw_affiliation_strings":["Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles, Beijing, China","School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles, Beijing, China","institution_ids":["https://openalex.org/I4210118977"]},{"raw_affiliation_string":"School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China","institution_ids":["https://openalex.org/I62853816"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008151152","display_name":"Linkai Ding","orcid":"https://orcid.org/0000-0003-2174-9929"},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]},{"id":"https://openalex.org/I4210118977","display_name":"Shanghai Tunnel Engineering Rail Transit Design & Research Institute","ror":"https://ror.org/02zznv955","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118977"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linkai Ding","raw_affiliation_strings":["Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles, Beijing, China","School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles, Beijing, China","institution_ids":["https://openalex.org/I4210118977"]},{"raw_affiliation_string":"School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China","institution_ids":["https://openalex.org/I62853816"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5002398665"],"corresponding_institution_ids":["https://openalex.org/I4210118977","https://openalex.org/I62853816"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.12755473,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"39","issue":"5","first_page":"7909","last_page":"7919"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9970999956130981,"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":0.9970999956130981,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9955000281333923,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9793000221252441,"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":0.7461987733840942},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.738609790802002},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6897836923599243},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6319414973258972},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.6008307933807373},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5827141404151917},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5649884343147278},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.5603188872337341},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5418641567230225},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5094383358955383},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.48037654161453247},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4693756103515625},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.4269307255744934},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3425816297531128},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.057990968227386475},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.05327674746513367}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7461987733840942},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.738609790802002},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6897836923599243},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6319414973258972},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.6008307933807373},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5827141404151917},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5649884343147278},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5603188872337341},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5418641567230225},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5094383358955383},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.48037654161453247},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4693756103515625},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.4269307255744934},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3425816297531128},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.057990968227386475},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.05327674746513367},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-201370","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-201370","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1993220166","https://openalex.org/W1996216253","https://openalex.org/W2053724458","https://openalex.org/W2080675694","https://openalex.org/W2113125055","https://openalex.org/W2125069507","https://openalex.org/W2148143831","https://openalex.org/W2157331557","https://openalex.org/W2252057809","https://openalex.org/W2257979135","https://openalex.org/W2306941105","https://openalex.org/W2464532507","https://openalex.org/W2562319768","https://openalex.org/W2584009249","https://openalex.org/W2606902231","https://openalex.org/W2619201468","https://openalex.org/W2802062301","https://openalex.org/W2836242602","https://openalex.org/W2902124116","https://openalex.org/W2951278869","https://openalex.org/W2964268978","https://openalex.org/W2968231406","https://openalex.org/W2968618166","https://openalex.org/W4298289240","https://openalex.org/W6637568146"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3005996785","https://openalex.org/W3014948380","https://openalex.org/W4386984417","https://openalex.org/W2476099471","https://openalex.org/W4380551139","https://openalex.org/W2280377497","https://openalex.org/W3174044702","https://openalex.org/W4238433571","https://openalex.org/W2967848559"],"abstract_inverted_index":{"The":[0],"purpose":[1],"of":[2,10,13,21,41,45,48,59,82,109,112,124,135,182,197],"sentiment":[3,14,18,159,194],"classification":[4,19,57,160,176,195],"is":[5,72,129],"to":[6,62,91,131,145,163],"solve":[7],"the":[8,17,28,39,42,46,56,60,70,78,86,100,107,110,118,121,142,147,152,158,165,172,193],"problem":[9],"automatic":[11],"judgment":[12],"tendency.":[15],"In":[16,67,77,117],"task":[20,196],"text":[22],"data":[23],"(such":[24],"as":[25],"online":[26],"reviews),":[27],"traditional":[29],"deep":[30,161,183],"learning":[31,184,190],"model":[32,61,162,166,173],"focuses":[33],"on":[34,187],"algorithm":[35],"optimization,":[36],"but":[37],"ignores":[38],"characteristics":[40],"imbalanced":[43,189],"distribution":[44,88],"number":[47],"samples":[49,81,111,134,144,154],"in":[50,64,85,115,178,192],"each":[51],"classification,":[52],"which":[53],"will":[54],"cause":[55],"performance":[58,177],"decrease":[63],"practical":[65],"applications.":[66],"this":[68],"paper,":[69],"experiment":[71],"divided":[73],"into":[74,157],"two":[75],"stages.":[76],"first":[79],"stage,":[80,120],"minority":[83,113,136],"class":[84,114,137],"sample":[87,148],"are":[89,155],"used":[90,130],"train":[92],"a":[93,180],"sequence":[94,101,125],"generative":[95,102,126],"adversarial":[96,103,127],"nets,":[97],"so":[98],"that":[99,171],"nets":[104,128],"can":[105],"learn":[106],"features":[108],"depth.":[116],"second":[119],"trained":[122],"generator":[123],"generate":[132],"false":[133],"and":[138],"mix":[139],"them":[140],"with":[141],"original":[143],"balance":[146],"distribution.":[149],"After":[150],"that,":[151],"mixed":[153],"input":[156],"complete":[164],"training.":[167],"Experimental":[168],"results":[169],"show":[170],"has":[174],"excellent":[175],"comparing":[179],"variety":[181],"models":[185],"based":[186],"classic":[188],"methods":[191],"hotel":[198],"reviews.":[199]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
