{"id":"https://openalex.org/W3201057333","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533770","title":"Improving Multi-Category Sentiment Classification by Semantic Dual-Granularity and Syntax-Path Encoding","display_name":"Improving Multi-Category Sentiment Classification by Semantic Dual-Granularity and Syntax-Path Encoding","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3201057333","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533770","mag":"3201057333"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533770","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533770","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5058464388","display_name":"Zongyuan Li","orcid":"https://orcid.org/0000-0003-3567-6978"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zong-Yuan Li","raw_affiliation_strings":["School of Computer Science, Wuhan university, WuHan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan university, WuHan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013785156","display_name":"Junwei Bao","orcid":"https://orcid.org/0000-0002-5549-5130"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun-Wei Bao","raw_affiliation_strings":["School of Computer Science, Wuhan university, WuHan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan university, WuHan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047240103","display_name":"Bo Han","orcid":"https://orcid.org/0000-0002-6338-0958"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Han","raw_affiliation_strings":["School of Computer Science, Wuhan university, WuHan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan university, WuHan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"1","last_page":"8"},"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":0.9994000196456909,"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":0.9991999864578247,"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":0.8513106107711792},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6975895762443542},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6503419280052185},{"id":"https://openalex.org/keywords/syntax","display_name":"Syntax","score":0.6318743228912354},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6073133945465088},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5773199200630188},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.5760399103164673},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.574966549873352},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.503131091594696},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4910755157470703},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.48997369408607483},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43160945177078247},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.07668814063072205}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8513106107711792},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6975895762443542},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6503419280052185},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.6318743228912354},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6073133945465088},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5773199200630188},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.5760399103164673},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.574966549873352},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.503131091594696},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4910755157470703},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.48997369408607483},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43160945177078247},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.07668814063072205},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533770","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533770","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7491501122","display_name":null,"funder_award_id":"U1531122","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8693496991","display_name":null,"funder_award_id":"2018YFB1702703","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1536516100","https://openalex.org/W1632114991","https://openalex.org/W2108420397","https://openalex.org/W2123442489","https://openalex.org/W2126502509","https://openalex.org/W2136891251","https://openalex.org/W2149684865","https://openalex.org/W2166706824","https://openalex.org/W2170240176","https://openalex.org/W2250966211","https://openalex.org/W2252215182","https://openalex.org/W2252223413","https://openalex.org/W2265846598","https://openalex.org/W2571563030","https://openalex.org/W2781548983","https://openalex.org/W2799100448","https://openalex.org/W2893235790","https://openalex.org/W2900541741","https://openalex.org/W2901078833","https://openalex.org/W2951727499","https://openalex.org/W2962802054","https://openalex.org/W2962902802","https://openalex.org/W2963012544","https://openalex.org/W2963403868","https://openalex.org/W2963956654","https://openalex.org/W2970261805","https://openalex.org/W2971036683","https://openalex.org/W3114508904","https://openalex.org/W4385245566","https://openalex.org/W6632166289","https://openalex.org/W6676253775","https://openalex.org/W6685053522","https://openalex.org/W6691421013","https://openalex.org/W6693505360","https://openalex.org/W6732001033","https://openalex.org/W6739901393","https://openalex.org/W6747313013"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W2999756192","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2059697060","https://openalex.org/W936373746","https://openalex.org/W2975817033","https://openalex.org/W4382701072"],"abstract_inverted_index":{"Semantic":[0],"features,":[1],"word":[2,31,89],"sequences,":[3,32],"and":[4,30,40,55,63,90,158,187,194],"syntactic":[5,35,114,118,128],"structures":[6],"are":[7,88],"three":[8,49,156],"key":[9,50,108],"elements":[10,51],"for":[11,66,147],"human":[12],"classification":[13,21,42],"of":[14,179,185,191],"multi-category":[15,67,148,160],"sentiment":[16,20,68,149,161],"texts.":[17],"However,":[18],"current":[19],"neural":[22,129],"network":[23],"models":[24,144,173],"focus":[25],"mostly":[26],"on":[27,196],"semantic":[28,61,74,84],"features":[29,119],"thereby":[33],"losing":[34],"structure":[36],"information":[37],"in":[38,110],"modeling":[39],"limiting":[41],"accuracy.":[43],"In":[44,70],"this":[45],"paper,":[46],"we":[47,76,94,116],"combine":[48],"at":[52,72],"different":[53],"levels":[54],"propose":[56],"an":[57,137],"enhanced":[58],"model":[59,154,167],"with":[60,174],"dual-granularity":[62,85],"syntax-path":[64],"encoding":[65,121],"classification.":[69,150],"particular,":[71],"the":[73,96,101,113,141],"level,":[75,115],"utilized":[77],"two":[78,97,142],"long":[79],"short-term":[80],"memories":[81],"to":[82,104,132,155],"process":[83],"units":[86],"that":[87],"n-gram":[91],"sequences;":[92],"then":[93],"combined":[95,146],"memory":[98],"outputs":[99],"via":[100],"attention":[102],"mechanism":[103],"highlight":[105],"keywords":[106],"or":[107],"phrases":[109],"sentences.":[111],"At":[112],"extracted":[117],"by":[120],"each":[122,197],"word's":[123],"syntax":[124],"path":[125],"into":[126],"a":[127,175,181],"network,":[130],"aiming":[131],"capture":[133],"implied":[134],"sentiments":[135],"through":[136],"expression":[138],"pattern.":[139],"Finally,":[140],"levels'":[143],"were":[145],"We":[151],"applied":[152],"our":[153,166],"common":[157],"public":[159],"datasets.":[162],"Experimental":[163],"results":[164],"showed":[165],"significantly":[168],"outperforming":[169],"eight":[170],"strong":[171],"baseline":[172],"maximum":[176],"accuracy":[177,183,189],"improvement":[178,184],"48.8%;":[180],"minimum":[182],"1%;":[186],"average":[188],"improvements":[190],"20.9%,":[192],"19.3%,":[193],"14.8%":[195],"dataset,":[198],"respectively.":[199]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
