{"id":"https://openalex.org/W4387822525","doi":"https://doi.org/10.3233/jifs-230537","title":"Research on sentiment analysis methods based on aspect word embedding graph convolutional networks","display_name":"Research on sentiment analysis methods based on aspect word embedding graph convolutional networks","publication_year":2023,"publication_date":"2023-10-20","ids":{"openalex":"https://openalex.org/W4387822525","doi":"https://doi.org/10.3233/jifs-230537"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-230537","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-230537","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/A5110376346","display_name":"Qiuyue Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiuyue Wei","raw_affiliation_strings":["School of Automation, Xi\u2019an Robertic Intelligent Systems International Science and Technology Cooperation Base, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, Shaanxi, China","School of Automation, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, China","School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Xi\u2019an Robertic Intelligent Systems International Science and Technology Cooperation Base, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, Shaanxi, China","institution_ids":["https://openalex.org/I4210136859"]},{"raw_affiliation_string":"School of Automation, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, China","institution_ids":["https://openalex.org/I4210136859"]},{"raw_affiliation_string":"School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109957230","display_name":"Dong Sheng Yang","orcid":"https://orcid.org/0009-0004-6032-7280"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Yang","raw_affiliation_strings":["School of Automation, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, China","School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, China","institution_ids":["https://openalex.org/I4210136859"]},{"raw_affiliation_string":"School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100350849","display_name":"Mingjie Zhang","orcid":"https://orcid.org/0000-0001-9404-0190"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mingjie Zhang","raw_affiliation_strings":["School of Economics and Management, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, China","School of Economics and Management, Xi'an University of Posts and Telecommunications, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, China","institution_ids":["https://openalex.org/I4210136859"]},{"raw_affiliation_string":"School of Economics and Management, Xi'an University of Posts and Telecommunications, Xi'an, China","institution_ids":["https://openalex.org/I4210136859"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100350849"],"corresponding_institution_ids":["https://openalex.org/I4210136859"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13786426,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"45","issue":"6","first_page":"11949","last_page":"11962"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T10028","display_name":"Topic Modeling","score":0.9962000250816345,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9961000084877014,"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":0.8465050458908081},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6800709366798401},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.5781644582748413},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5610870122909546},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5589656233787537},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5400896668434143},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5319989323616028},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.47955891489982605},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4391574561595917},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.43093812465667725},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.23901477456092834}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8465050458908081},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6800709366798401},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.5781644582748413},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5610870122909546},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5589656233787537},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5400896668434143},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5319989323616028},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.47955891489982605},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4391574561595917},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.43093812465667725},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.23901477456092834},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-230537","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-230537","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":23,"referenced_works":["https://openalex.org/W2064675550","https://openalex.org/W2251124635","https://openalex.org/W2251648804","https://openalex.org/W2734502597","https://openalex.org/W2896457183","https://openalex.org/W2901440799","https://openalex.org/W2997013919","https://openalex.org/W2998446468","https://openalex.org/W2998704965","https://openalex.org/W3034492151","https://openalex.org/W3208152475","https://openalex.org/W3210828003","https://openalex.org/W3214174720","https://openalex.org/W4288346886","https://openalex.org/W4312552362","https://openalex.org/W6680532216","https://openalex.org/W6691216643","https://openalex.org/W6691410720","https://openalex.org/W6755207826","https://openalex.org/W6756250085","https://openalex.org/W6770754383","https://openalex.org/W6779961489","https://openalex.org/W6782886300"],"related_works":["https://openalex.org/W2548633793","https://openalex.org/W3089396779","https://openalex.org/W3186997021","https://openalex.org/W2997097677","https://openalex.org/W4200618314","https://openalex.org/W4308088897","https://openalex.org/W2911655849","https://openalex.org/W2771357047","https://openalex.org/W4286432911","https://openalex.org/W3134737443"],"abstract_inverted_index":{"Aspect-based":[0],"sentiment":[1,11],"analysis":[2],"is":[3,71,81,114,120,127],"a":[4,75,101],"fine-grained":[5],"task":[6,157],"in":[7,83,100],"the":[8,27,35,62,67,78,84,87,92,106,111,130,164],"field":[9],"of":[10,30,37,41,61,86,166],"analysis.":[12],"Various":[13],"GCN":[14],"approaches":[15,25],"have":[16],"recently":[17],"emerged":[18],"to":[19,57,155],"work":[20],"on":[21,142],"this,":[22],"but":[23],"many":[24],"ignored":[26],"critical":[28],"role":[29],"aspectual":[31],"word":[32,48],"information":[33,64,69,80,113],"and":[34,65,146,151,158],"effect":[36,94],"noise.":[38],"In":[39,55],"view":[40],"this":[42,156],"situation,":[43],"we":[44,147],"propose":[45],"an":[46,123],"aspect-based":[47],"embedding":[49],"graph":[50,108],"convolutional":[51,109],"network":[52],"(AWEGCN)":[53],"model.":[54,168],"order":[56],"make":[58],"good":[59],"use":[60],"aspect":[63,79,97,112],"distinguish":[66],"contextual":[68,118],"that":[70,136,162],"more":[72],"important":[73],"for":[74],"particular":[76],"aspect,":[77],"embedded":[82],"output":[85],"hidden":[88],"layer.":[89],"To":[90],"reduce":[91],"noise":[93],"when":[95],"multiple":[96],"words":[98],"appear":[99],"sentence,":[102],"after":[103],"going":[104],"through":[105,122],"bidirectional":[107],"network,":[110],"embedded.":[115],"A":[116],"specific":[117],"representation":[119],"computed":[121],"attention":[124],"mechanism,":[125],"which":[126],"used":[128],"as":[129],"final":[131],"classification":[132],"feature.":[133],"Experiments":[134],"show":[135],"our":[137,167],"model":[138],"achieves":[139],"impressive":[140],"performance":[141],"five":[143],"public":[144],"datasets,":[145],"also":[148],"apply":[149],"BERT":[150],"XLNet":[152],"pre-trained":[153],"models":[154],"obtain":[159],"advanced":[160],"results":[161],"validate":[163],"effectiveness":[165]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
