乐胖代购免代理版

{"id":"https://openalex.org/W4312552362","doi":"https://doi.org/10.1109/access.2022.3214233","title":"Aspect-Level Sentiment Analysis Using CNN Over BERT-GCN","display_name":"Aspect-Level Sentiment Analysis Using CNN Over BERT-GCN","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312552362","doi":"https://doi.org/10.1109/access.2022.3214233"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3214233","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09918053.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09918053.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028824441","display_name":"Huyen Trang Phan","orcid":"https://orcid.org/0000-0002-7466-9562"},"institutions":[{"id":"https://openalex.org/I55240360","display_name":"Yeungnam University","ror":"https://ror.org/05yc6p159","country_code":"KR","type":"education","lineage":["https://openalex.org/I55240360"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Huyen Trang Phan","raw_affiliation_strings":["Department of Computer Engineering, Yeungnam University, Gyeongsan, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Yeungnam University, Gyeongsan, Republic of Korea","institution_ids":["https://openalex.org/I55240360"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047517734","display_name":"Ngoc Thanh Nguy\u00ean","orcid":"https://orcid.org/0000-0002-3247-2948"},"institutions":[{"id":"https://openalex.org/I11923345","display_name":"Wroc\u0142aw University of Science and Technology","ror":"https://ror.org/008fyn775","country_code":"PL","type":"education","lineage":["https://openalex.org/I11923345"]},{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]},{"id":"https://openalex.org/I3020192730","display_name":"Tr\u01b0\u1eddng \u0110H Nguy\u1ec5n T\u1ea5t Th\u00e0nh","ror":"https://ror.org/04r9s1v23","country_code":"VN","type":"education","lineage":["https://openalex.org/I3020192730"]}],"countries":["PL","VN"],"is_corresponding":false,"raw_author_name":"Ngoc Thanh Nguyen","raw_affiliation_strings":["Faculty of Computer Science and Management, Wroclaw University of Science and Technology, Wroclaw, Poland","Faculty of Information Technology, Nguyen Tat Thanh University, Vietnam"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science and Management, Wroclaw University of Science and Technology, Wroclaw, Poland","institution_ids":["https://openalex.org/I11923345","https://openalex.org/I686019"]},{"raw_affiliation_string":"Faculty of Information Technology, Nguyen Tat Thanh University, Vietnam","institution_ids":["https://openalex.org/I3020192730"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032265881","display_name":"Dosam Hwang","orcid":"https://orcid.org/0000-0001-7851-7323"},"institutions":[{"id":"https://openalex.org/I55240360","display_name":"Yeungnam University","ror":"https://ror.org/05yc6p159","country_code":"KR","type":"education","lineage":["https://openalex.org/I55240360"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dosam Hwang","raw_affiliation_strings":["Department of Computer Engineering, Yeungnam University, Gyeongsan, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Yeungnam University, Gyeongsan, Republic of Korea","institution_ids":["https://openalex.org/I55240360"]}]}],"institution_assertions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850,"provenance":"doaj"},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850,"provenance":"doaj"},"fwci":3.813,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.694314,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"10","issue":null,"first_page":"110402","last_page":"110409"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998,"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":0.9998,"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":"Automatic Keyword Extraction from Textual Data","score":0.9923,"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":"Multi-label Text Classification in Machine Learning","score":0.992,"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/aspect-based-sentiment-analysis","display_name":"Aspect-based Sentiment Analysis","score":0.585211},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment Analysis","score":0.561464},{"id":"https://openalex.org/keywords/twitter-sentiment","display_name":"Twitter Sentiment","score":0.548035},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion Recognition","score":0.506336},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41015306}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.9053012},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.82942796},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.57639945},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.56193024},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.54213},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.44709063},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.43822986},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41015306},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.105175346},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3214233","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09918053.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":false,"landing_page_url":"https://doaj.org/article/4f1bc698627e491db1810226dce3b4ee","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3214233","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09918053.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, justice, and strong institutions","score":0.47}],"grants":[{"funder":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea","award_id":"4299990214225"}],"datasets":[],"versions":[],"referenced_works_count":26,"referenced_works":["https://openalex.org/W1532325895","https://openalex.org/W1940872118","https://openalex.org/W2079735306","https://openalex.org/W2251124635","https://openalex.org/W2251648804","https://openalex.org/W2529550020","https://openalex.org/W2562607067","https://openalex.org/W2896457183","https://openalex.org/W2962946486","https://openalex.org/W2963909901","https://openalex.org/W2964015378","https://openalex.org/W2964121744","https://openalex.org/W2964164368","https://openalex.org/W2970748008","https://openalex.org/W2971220558","https://openalex.org/W2975429091","https://openalex.org/W2977572677","https://openalex.org/W2985331920","https://openalex.org/W2989092762","https://openalex.org/W2997013919","https://openalex.org/W3003963580","https://openalex.org/W3044187822","https://openalex.org/W3045825587","https://openalex.org/W3088886232","https://openalex.org/W3113712958","https://openalex.org/W4205721122"],"related_works":["https://openalex.org/W4317653575","https://openalex.org/W4301373556","https://openalex.org/W4286571989","https://openalex.org/W4224284088","https://openalex.org/W3132372214","https://openalex.org/W3089396779","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W2596247554","https://openalex.org/W2548633793"],"abstract_inverted_index":{"The":[0,179],"increase":[1],"in":[2,12,41,54,142,194,202],"the":[3,21,42,67,90,99,106,112,119,126,131,190,196,205],"volume":[4],"of":[5,23,37,44,69,79,92,105,115,122,128,133,177,198,204],"user-generated":[6],"content":[7],"on":[8,152,185],"Twitter":[9,26],"has":[10,32,73,182],"resulted":[11],"tweet":[13,38,70,93,199],"sentiment":[14,39,49,71,94,120,137,162,175,200],"analysis":[15,40,50,72,95,201],"becoming":[16],"an":[17,77],"essential":[18],"tool":[19],"for":[20,81],"extraction":[22],"information":[24,114],"about":[25],"users\u2019":[27],"emotional":[28],"state.":[29],"Consequently,":[30],"there":[31],"been":[33,140,183],"a":[34,148,153],"rapid":[35],"growth":[36],"area":[43,78],"natural":[45],"language":[46],"processing.":[47],"Tweet":[48],"is":[51],"increasingly":[52],"applied":[53],"many":[55,82,143],"areas,":[56],"such":[57,168],"as":[58,169],"decision":[59],"support":[60],"systems":[61],"and":[62,76,130,174,189],"recommendation":[63],"systems.":[64],"Therefore,":[65],"improving":[66,195],"accuracy":[68],"become":[74],"practical":[75],"interest":[80],"researchers.":[83],"Many":[84],"approaches":[85],"have":[86,138],"tried":[87],"to":[88,110,158],"improve":[89],"performance":[91,197],"methods":[96,108],"by":[97,163],"using":[98],"feature":[100,154],"ensemble":[101,155],"method.":[102],"However,":[103],"most":[104],"previous":[107],"attempted":[109],"model":[111,156],"syntactic":[113],"words":[116,129],"without":[117],"considering":[118],"context":[121],"these":[123],"words.":[124,178],"Besides,":[125],"positioning":[127],"impact":[132],"phrases":[134],"containing":[135,160],"fuzzy":[136,161],"not":[139],"mentioned":[141],"studies.":[144],"This":[145],"study":[146],"proposed":[147,180],"new":[149],"approach":[150],"based":[151],"related":[157],"tweets":[159],"taking":[164],"into":[165],"account":[166],"elements":[167],"lexical,":[170],"word-type,":[171],"semantic,":[172],"position,":[173],"polarity":[176],"method":[181],"experimented":[184],"with":[186],"real":[187],"data,":[188],"result":[191],"proves":[192],"effective":[193],"terms":[203],"F":[208],"1":[211],"score.":[212]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4312552362","counts_by_year":[{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":11}],"updated_date":"2024-11-30T22:32:15.044459","created_date":"2023-01-05"}