{"id":"https://openalex.org/W4316660679","doi":"https://doi.org/10.1109/taffc.2023.3236948","title":"Hybrid Regularizations for Multi-Aspect Category Sentiment Analysis","display_name":"Hybrid Regularizations for Multi-Aspect Category Sentiment Analysis","publication_year":2023,"publication_date":"2023-01-16","ids":{"openalex":"https://openalex.org/W4316660679","doi":"https://doi.org/10.1109/taffc.2023.3236948"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2023.3236948","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2023.3236948","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"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 Transactions on Affective Computing","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/A5048141765","display_name":"Mengting Hu","orcid":"https://orcid.org/0000-0003-1536-5400"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengting Hu","raw_affiliation_strings":["College of Software, Nankai University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-1536-5400","affiliations":[{"raw_affiliation_string":"College of Software, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052465353","display_name":"Shiwan Zhao","orcid":"https://orcid.org/0000-0001-5068-025X"},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiwan Zhao","raw_affiliation_strings":["Natural Language Processing Group, IBM China Research China Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5068-025X","affiliations":[{"raw_affiliation_string":"Natural Language Processing Group, IBM China Research China Beijing, Beijing, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001909797","display_name":"Honglei Guo","orcid":"https://orcid.org/0000-0002-1485-1987"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Honglei Guo","raw_affiliation_strings":["Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1485-1987","affiliations":[{"raw_affiliation_string":"Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010426520","display_name":"Zhong Su","orcid":"https://orcid.org/0000-0003-2303-9787"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Su","raw_affiliation_strings":["Alibaba Research, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alibaba Research, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3053,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.83461079,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"14","issue":"4","first_page":"3294","last_page":"3304"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9890999794006348,"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":0.9775999784469604,"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/sentiment-analysis","display_name":"Sentiment analysis","score":0.654036819934845},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.431529700756073},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40776193141937256},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3822261095046997},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.3358458876609802}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.654036819934845},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.431529700756073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40776193141937256},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3822261095046997},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3358458876609802}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taffc.2023.3236948","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2023.3236948","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"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 Transactions on Affective Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1934455055","https://openalex.org/W2064675550","https://openalex.org/W2097499525","https://openalex.org/W2105482032","https://openalex.org/W2146502635","https://openalex.org/W2250539671","https://openalex.org/W2251294039","https://openalex.org/W2252057809","https://openalex.org/W2465978385","https://openalex.org/W2562607067","https://openalex.org/W2567698949","https://openalex.org/W2606593809","https://openalex.org/W2767210791","https://openalex.org/W2767439512","https://openalex.org/W2783477514","https://openalex.org/W2788810909","https://openalex.org/W2789561036","https://openalex.org/W2804000041","https://openalex.org/W2808182015","https://openalex.org/W2891778157","https://openalex.org/W2896457183","https://openalex.org/W2898642169","https://openalex.org/W2903110172","https://openalex.org/W2908490889","https://openalex.org/W2914278227","https://openalex.org/W2962808042","https://openalex.org/W2963240575","https://openalex.org/W2963303028","https://openalex.org/W2964164368","https://openalex.org/W2970038129","https://openalex.org/W2970692876","https://openalex.org/W2970748008","https://openalex.org/W2974612674","https://openalex.org/W3092050587","https://openalex.org/W3092282657","https://openalex.org/W3106213915","https://openalex.org/W3109277142","https://openalex.org/W3175246058","https://openalex.org/W3176038554","https://openalex.org/W3176719207","https://openalex.org/W4211186029","https://openalex.org/W4239943352","https://openalex.org/W4285306086","https://openalex.org/W4385573331","https://openalex.org/W6681435938","https://openalex.org/W6697121895","https://openalex.org/W6747116778","https://openalex.org/W6757593157"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W2596247554","https://openalex.org/W3132372214","https://openalex.org/W4224284088","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Aspect":[0],"level":[1],"sentiment":[2,8,33,78],"classification":[3],"aims":[4],"to":[5,30,118],"identify":[6],"the":[7,32,44,51,59,62,72,93,111,115,174,177],"polarity":[9],"towards":[10],"a":[11,15],"particular":[12],"aspect":[13,26,152],"in":[14,43,47,85,180],"sentence.":[16],"Previous":[17],"attention-based":[18],"methods":[19],"generate":[20],"an":[21,147],"aspect-specific":[22],"representation":[23],"for":[24,77,127,134,162],"each":[25],"and":[27,57,104,130,183],"employ":[28],"it":[29],"classify":[31],"polarity.":[34],"However,":[35],"normalized":[36],"attention":[37,52,116],"scores":[38],"scatter":[39],"over":[40],"every":[41],"word":[42],"sentence,":[45],"resulting":[46],"two":[48,95],"issues.":[49],"First,":[50],"may":[53,65],"inherently":[54],"introduce":[55],"noise":[56],"downgrade":[58],"performance.":[60],"Second,":[61],"opinion":[63,73],"words":[64],"be":[66],"\u201cdiluted\u201d":[67],"by":[68,145],"other":[69],"words,":[70],"while":[71],"feature":[74],"should":[75],"dominate":[76],"analysis.":[79],"The":[80],"issues":[81,96],"become":[82],"more":[83],"severe":[84],"multi-aspect":[86,128],"sentences.":[87,136],"In":[88],"this":[89],"paper,":[90],"we":[91],"address":[92],"above":[94],"via":[97],"hybrid":[98],"regularizations,":[99],"i.e.,":[100,151],"<italic":[101,105],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[102,106],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">aspect-level</i>":[103],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">task-level":[107],"regularizations</i>":[108],".":[109],"Concretely,":[110],"aspect-level":[112],"regularizations":[113],"constrain":[114],"weights":[117],"alleviate":[119],"noise.":[120],"Among":[121],"them,":[122],"orthogonal":[123,148],"regularization":[124,132,142,156],"is":[125,133,143],"designed":[126],"sentences":[129],"sparse":[131],"single-aspect":[135],"To":[137],"extract":[138],"sentiment-dominant":[139],"features,":[140],"task-level":[141],"proposed":[144,178],"introducing":[146],"auxiliary":[149],"task,":[150],"category":[153],"detection.":[154],"This":[155],"can":[157],"allocate":[158],"task-oriented":[159],"context":[160],"information":[161],"specific":[163],"downstream":[164],"tasks.":[165],"Extensive":[166],"experimental":[167],"results":[168],"on":[169],"three":[170],"public":[171],"datasets":[172],"demonstrate":[173],"effectiveness":[175],"of":[176],"approach":[179],"both":[181],"single-task":[182],"multi-task":[184],"scenarios.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}