{"id":"https://openalex.org/W3109016349","doi":"https://doi.org/10.1109/mis.2020.3042253","title":"GSMNet: Global Semantic Memory Network for Aspect-Level Sentiment Classification","display_name":"GSMNet: Global Semantic Memory Network for Aspect-Level Sentiment Classification","publication_year":2020,"publication_date":"2020-12-03","ids":{"openalex":"https://openalex.org/W3109016349","doi":"https://doi.org/10.1109/mis.2020.3042253","mag":"3109016349"},"language":"en","primary_location":{"id":"doi:10.1109/mis.2020.3042253","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mis.2020.3042253","pdf_url":null,"source":{"id":"https://openalex.org/S114241109","display_name":"IEEE Intelligent Systems","issn_l":"1541-1672","issn":["1541-1672","1941-1294"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Intelligent 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/A5010737776","display_name":"Zhiyue Liu","orcid":"https://orcid.org/0000-0001-6432-7836"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhiyue Liu","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101698803","display_name":"Jiahai Wang","orcid":"https://orcid.org/0000-0002-6961-7813"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahai Wang","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072622280","display_name":"Xin Du","orcid":"https://orcid.org/0000-0002-0461-9682"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Du","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058291454","display_name":"Yanghui Rao","orcid":"https://orcid.org/0000-0003-1610-9599"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanghui Rao","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040062188","display_name":"Xiaojun Quan","orcid":"https://orcid.org/0000-0002-8385-1083"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojun Quan","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5010737776"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":1.3256,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.85164523,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"36","issue":"5","first_page":"122","last_page":"130"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9962999820709229,"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":0.9954000115394592,"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":0.8784317374229431},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6209693551063538},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.602253258228302},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5804653763771057},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.53119295835495},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.5306569337844849},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5128645896911621},{"id":"https://openalex.org/keywords/semantic-memory","display_name":"Semantic memory","score":0.49456068873405457},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.48784422874450684},{"id":"https://openalex.org/keywords/semantic-computing","display_name":"Semantic computing","score":0.4767516553401947},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4738143980503082},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.4527266025543213},{"id":"https://openalex.org/keywords/semantic-web","display_name":"Semantic Web","score":0.15773892402648926},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.07079625129699707}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8784317374229431},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6209693551063538},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.602253258228302},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5804653763771057},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.53119295835495},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.5306569337844849},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5128645896911621},{"id":"https://openalex.org/C197914299","wikidata":"https://www.wikidata.org/wiki/Q18650","display_name":"Semantic memory","level":3,"score":0.49456068873405457},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.48784422874450684},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.4767516553401947},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4738143980503082},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.4527266025543213},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.15773892402648926},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.07079625129699707},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/mis.2020.3042253","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mis.2020.3042253","pdf_url":null,"source":{"id":"https://openalex.org/S114241109","display_name":"IEEE Intelligent Systems","issn_l":"1541-1672","issn":["1541-1672","1941-1294"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Intelligent Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4000000059604645}],"awards":[{"id":"https://openalex.org/G3131683276","display_name":null,"funder_award_id":"61673403","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3431216509","display_name":null,"funder_award_id":"U1611262","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4233013071","display_name":null,"funder_award_id":"2018AAA0101203","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G710202329","display_name":null,"funder_award_id":"62072483","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation 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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2113125055","https://openalex.org/W2242874043","https://openalex.org/W2250539671","https://openalex.org/W2250851590","https://openalex.org/W2251124635","https://openalex.org/W2251648804","https://openalex.org/W2252057809","https://openalex.org/W2296071000","https://openalex.org/W2562607067","https://openalex.org/W2601148979","https://openalex.org/W2757541972","https://openalex.org/W2785994986","https://openalex.org/W2786411768","https://openalex.org/W2788347302","https://openalex.org/W2788810909","https://openalex.org/W2887856105","https://openalex.org/W2891778157","https://openalex.org/W2896457183","https://openalex.org/W2896774156","https://openalex.org/W2962692632","https://openalex.org/W2962741379","https://openalex.org/W2963168371","https://openalex.org/W2963240575","https://openalex.org/W2964164368","https://openalex.org/W2978855205","https://openalex.org/W3094173182","https://openalex.org/W6676723433","https://openalex.org/W6697121895","https://openalex.org/W6748053814","https://openalex.org/W6748560189","https://openalex.org/W6755207826"],"related_works":["https://openalex.org/W1965623300","https://openalex.org/W3134365128","https://openalex.org/W2541135911","https://openalex.org/W2359259132","https://openalex.org/W2624542985","https://openalex.org/W4387489691","https://openalex.org/W2156467700","https://openalex.org/W2114077504","https://openalex.org/W2103835134","https://openalex.org/W2807098362"],"abstract_inverted_index":{"Aspect-level":[0],"sentiment":[1,5],"classification":[2],"determines":[3],"the":[4,23,26,39,54,86,99,116,132,139,149],"polarity":[6],"of":[7,56,90,101,114,134,142,151],"a":[8,32,75,95,125],"targeted":[9],"aspect.":[10],"To":[11],"solve":[12],"this":[13],"task,":[14],"attention-based":[15],"neural":[16],"networks":[17],"are":[18],"typically":[19],"adopted":[20],"to":[21,84,130],"explore":[22],"interaction":[24],"between":[25],"aspect":[27],"and":[28,93],"its":[29],"context":[30],"in":[31],"single":[33],"sentence.":[34],"However,":[35],"such":[36],"approaches":[37],"ignore":[38],"rich":[40],"semantic":[41,65,78,88],"information":[42,66,89,127],"that":[43,53,67],"can":[44,68,106],"be":[45,62,69,107],"obtained":[46],"from":[47],"other":[48],"sentences.":[49],"This":[50],"article":[51],"shows":[52],"contexts":[55],"aspects":[57,92],"with":[58],"similar":[59],"meanings":[60],"should":[61],"considered":[63],"global":[64,77,87],"incorporated":[70],"as":[71],"domain":[72,102],"knowledge.":[73],"Then,":[74],"novel":[76],"memory":[79],"network":[80],"(GSMNet)":[81],"is":[82],"proposed":[83],"share":[85],"various":[91],"generate":[94],"domain-specific":[96],"representation.":[97],"With":[98],"help":[100],"knowledge,":[103],"crucial":[104],"words":[105],"focused":[108],"on":[109],"more":[110],"precisely.":[111],"Moreover,":[112],"instead":[113],"employing":[115],"concatenating":[117],"operation":[118],"for":[119,136],"vectors":[120],"before":[121],"classification,":[122],"GSMNet":[123],"adopts":[124],"fine-grained":[126],"fusion":[128],"layer":[129],"capture":[131],"importance":[133],"representations":[135],"efficiently":[137],"extracting":[138],"valid":[140],"parts":[141],"each":[143],"dimension.":[144],"The":[145],"experimental":[146],"results":[147],"demonstrate":[148],"effectiveness":[150],"our":[152],"model.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
