{"id":"https://openalex.org/W3130007472","doi":"https://doi.org/10.1109/taslp.2021.3058540","title":"Deep Selective Memory Network With Selective Attention and Inter-Aspect Modeling for Aspect Level Sentiment Classification","display_name":"Deep Selective Memory Network With Selective Attention and Inter-Aspect Modeling for Aspect Level Sentiment Classification","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3130007472","doi":"https://doi.org/10.1109/taslp.2021.3058540","mag":"3130007472"},"language":"en","primary_location":{"id":"doi:10.1109/taslp.2021.3058540","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2021.3058540","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"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/ACM Transactions on Audio, Speech, and Language Processing","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/A5014957657","display_name":"Peiqin Lin","orcid":"https://orcid.org/0000-0003-2818-3008"},"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":"Peiqin Lin","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037873810","display_name":"Meng Yang","orcid":"https://orcid.org/0000-0002-0795-3221"},"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":"Meng Yang","raw_affiliation_strings":["Key Laboratory of Machine Intelligence and Advanced Computing, Sun Yat-sen University, Ministry of Education, China","School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Intelligence and Advanced Computing, Sun Yat-sen University, Ministry of Education, China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034685928","display_name":"Jianhuang Lai","orcid":"https://orcid.org/0000-0003-3883-2024"},"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":"Jianhuang Lai","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5014957657"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":2.5834,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.91112414,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":"29","issue":null,"first_page":"1093","last_page":"1106"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":1.0,"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":1.0,"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":0.9979000091552734,"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":0.9965000152587891,"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":0.8450825214385986},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.550259530544281},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5432778596878052},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5326732397079468},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.45693957805633545},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.44949716329574585}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8450825214385986},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.550259530544281},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5432778596878052},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5326732397079468},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.45693957805633545},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.44949716329574585},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taslp.2021.3058540","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2021.3058540","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"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/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G3031428753","display_name":null,"funder_award_id":"61772568","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4834643226","display_name":null,"funder_award_id":"18lgzd15","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W1501931667","https://openalex.org/W1522301498","https://openalex.org/W1614298861","https://openalex.org/W1793121960","https://openalex.org/W2113125055","https://openalex.org/W2133564696","https://openalex.org/W2148506018","https://openalex.org/W2152571774","https://openalex.org/W2154352106","https://openalex.org/W2159457224","https://openalex.org/W2165855670","https://openalex.org/W2250539671","https://openalex.org/W2251124635","https://openalex.org/W2251648804","https://openalex.org/W2252024663","https://openalex.org/W2252057809","https://openalex.org/W2296071000","https://openalex.org/W2427312199","https://openalex.org/W2493916176","https://openalex.org/W2529550020","https://openalex.org/W2562607067","https://openalex.org/W2740567223","https://openalex.org/W2756816896","https://openalex.org/W2757541972","https://openalex.org/W2767439512","https://openalex.org/W2788810909","https://openalex.org/W2789190634","https://openalex.org/W2799009183","https://openalex.org/W2804000041","https://openalex.org/W2814589985","https://openalex.org/W2896786335","https://openalex.org/W2898642169","https://openalex.org/W2950577311","https://openalex.org/W2951008357","https://openalex.org/W2962741379","https://openalex.org/W2962808042","https://openalex.org/W2963168371","https://openalex.org/W2963240575","https://openalex.org/W2963428430","https://openalex.org/W2963626623","https://openalex.org/W2964059932","https://openalex.org/W2964164368","https://openalex.org/W2964308564","https://openalex.org/W2964401366","https://openalex.org/W3101751354","https://openalex.org/W6631190155","https://openalex.org/W6636510571","https://openalex.org/W6638318767","https://openalex.org/W6676723433","https://openalex.org/W6679434410","https://openalex.org/W6683046363","https://openalex.org/W6697121895","https://openalex.org/W6727807531","https://openalex.org/W6732742072","https://openalex.org/W6748560189","https://openalex.org/W6753114942","https://openalex.org/W6780493881","https://openalex.org/W6785439353"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W3089396779","https://openalex.org/W2130974462","https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W2028665553","https://openalex.org/W2086519370"],"abstract_inverted_index":{"Aspect":[0],"level":[1,48],"sentiment":[2,8,49],"classification":[3],"aims":[4],"to":[5,108,115,130],"recognize":[6],"the":[7,20,25,58,65,85,100,120,138,142,147],"polarity":[9],"of":[10,19,99,119,137,149],"each":[11],"aspect":[12,47,90],"term":[13],"in":[14,103],"a":[15,43,79],"sentence.":[16],"However,":[17],"most":[18],"existing":[21],"methods":[22],"usually":[23],"applied":[24],"attention":[26,67,81],"mechanism":[27,68,82],"over":[28],"position-weighted":[29],"memory":[30,60,75,102,105],"and":[31,69,91,134,156],"did":[32],"not":[33],"consider":[34],"inter-aspect":[35,71,121,127],"information.":[36,113],"To":[37],"address":[38],"these":[39],"issues,":[40],"we":[41,123],"propose":[42],"novel":[44],"framework":[45,151,162],"for":[46,62,141],"classification,":[50],"Deep":[51],"Selective":[52],"Memory":[53],"Network":[54],"(DSMN),":[55],"which":[56],"selects":[57],"context":[59,101,112],"dynamically":[61],"better":[63],"guiding":[64],"multi-hop":[66],"integrates":[70],"information":[72,87,136],"with":[73],"deep":[74],"network.":[76],"By":[77],"designing":[78],"selective":[80],"based":[83],"on":[84,96,152],"distance":[86],"between":[88],"an":[89],"its":[92],"context,":[93],"DSMN":[94],"focuses":[95],"different":[97,104],"parts":[98],"network":[106],"layers":[107],"capture":[109],"abundant":[110],"aspect-aware":[111],"Besides,":[114],"make":[116],"full":[117],"use":[118],"information,":[122],"also":[124],"design":[125],"effective":[126],"modeling":[128],"modules":[129],"generate":[131],"both":[132],"semantic":[133],"relation":[135],"nearby":[139],"aspects":[140],"desired":[143],"aspect.":[144],"We":[145],"evaluate":[146],"advantages":[148],"our":[150,161],"three":[153],"benchmark":[154],"datasets,":[155],"experiment":[157],"results":[158],"show":[159],"that":[160],"achieves":[163],"state-of-the-art":[164],"performance.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
