{"id":"https://openalex.org/W2963981024","doi":"https://doi.org/10.18653/v1/n19-1036","title":"A Variational Approach to Weakly Supervised Document-Level Multi-Aspect Sentiment Classification","display_name":"A Variational Approach to Weakly Supervised Document-Level Multi-Aspect Sentiment Classification","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2963981024","doi":"https://doi.org/10.18653/v1/n19-1036","mag":"2963981024"},"language":"en","primary_location":{"id":"doi:10.18653/v1/n19-1036","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/n19-1036","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 Conference of the North","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.18653/v1/n19-1036","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101403806","display_name":"Ziqian Zeng","orcid":"https://orcid.org/0000-0003-0060-7956"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ziqian Zeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080937886","display_name":"Wenxuan Zhou","orcid":"https://orcid.org/0000-0003-1199-885X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenxuan Zhou","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050353397","display_name":"Xin Liu","orcid":"https://orcid.org/0000-0001-9610-9526"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xin Liu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5020880385","display_name":"Yangqiu Song","orcid":"https://orcid.org/0000-0002-7818-6090"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yangqiu Song","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101403806"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.15064844,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.89746498,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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":0.995199978351593,"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":0.9911999702453613,"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":0.6189383268356323},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6174333095550537},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.596912145614624},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.5667906999588013},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.5131767392158508},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.40274694561958313},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.11896967887878418},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07035866379737854}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6189383268356323},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6174333095550537},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.596912145614624},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.5667906999588013},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.5131767392158508},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.40274694561958313},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.11896967887878418},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07035866379737854},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/v1/n19-1036","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/n19-1036","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 Conference of the North","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-99000","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-99000","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"},{"id":"pmh:oai:repository.ust.hk:1783.1-99000","is_oa":false,"landing_page_url":"http://lbdiscover.ust.hk/uresolver?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rfr_id=info:sid/HKUST:SPI&rft.genre=article&rft.issn=&rft.volume=&rft.issue=&rft.date=2019&rft.spage=386&rft.aulast=Zeng&rft.aufirst=&rft.atitle=A%20Variational%20Approach%20to%20Weakly%20Supervised%20Document-Level%20Multi-Aspect%20Sentiment%20Classification&rft.title=Proceedings%20of%20the%202019%20Conference%20of%20the%20North%20American%20Chapter%20of%20the%20Association%20for%20Computational%20Linguistics%3A%20Human%20Language%20Technologies","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"}],"best_oa_location":{"id":"doi:10.18653/v1/n19-1036","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/n19-1036","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 Conference of the North","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8299999833106995,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W1503259811","https://openalex.org/W1517771839","https://openalex.org/W1675450783","https://openalex.org/W1988585844","https://openalex.org/W2019207508","https://openalex.org/W2022204871","https://openalex.org/W2081375810","https://openalex.org/W2097048552","https://openalex.org/W2112744748","https://openalex.org/W2115613106","https://openalex.org/W2147880316","https://openalex.org/W2148966043","https://openalex.org/W2150956310","https://openalex.org/W2153579005","https://openalex.org/W2159457224","https://openalex.org/W2160409620","https://openalex.org/W2160660844","https://openalex.org/W2189472871","https://openalex.org/W2222512263","https://openalex.org/W2250275424","https://openalex.org/W2250861254","https://openalex.org/W2251044566","https://openalex.org/W2252024663","https://openalex.org/W2316153475","https://openalex.org/W2402144811","https://openalex.org/W2562607067","https://openalex.org/W2604205681","https://openalex.org/W2756816896","https://openalex.org/W2757541972","https://openalex.org/W2758481664","https://openalex.org/W2808182015","https://openalex.org/W2890931111","https://openalex.org/W2962843214","https://openalex.org/W2962897886","https://openalex.org/W2963068946","https://openalex.org/W2963168371","https://openalex.org/W2963233086","https://openalex.org/W2963428430","https://openalex.org/W2964072618","https://openalex.org/W2964164368","https://openalex.org/W3049711450"],"related_works":["https://openalex.org/W2548633793","https://openalex.org/W2941935829","https://openalex.org/W3089396779","https://openalex.org/W2596247554","https://openalex.org/W4301373556","https://openalex.org/W3013279174","https://openalex.org/W3132372214","https://openalex.org/W4224284088","https://openalex.org/W4286571989","https://openalex.org/W3204019825"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,26,93],"propose":[4],"a":[5,55,65,78,82,111],"variational":[6,105],"approach":[7],"to":[8,49,63,69,89,100,139],"weakly":[9,127],"supervised":[10,128,142],"document-level":[11],"multi-aspect":[12],"sentiment":[13,66,72,87,97,112],"classification.":[14],"Instead":[15],"of":[16,74,146],"using":[17,40],"user-generated":[18],"ratings":[19],"or":[20],"annotations":[21],"provided":[22],"by":[23,39,115],"domain":[24],"experts,":[25],"use":[27],"target-opinion":[28],"word":[29,34,53,57],"pairs":[30,35],"as":[31],"\u201csupervision.\u201d":[32],"These":[33],"can":[36,94,109,125,136],"be":[37,137],"extracted":[38],"dependency":[41],"parsers":[42],"and":[43,132,135],"simple":[44],"rules.":[45],"Our":[46],"objective":[47,91,102],"is":[48,62],"predict":[50,70],"an":[51],"opinion":[52],"given":[54,77],"target":[56],"while":[58],"our":[59,123],"ultimate":[60],"goal":[61],"learn":[64,110],"polarity":[67,73,98,113],"classifier":[68,99,114],"the":[71,86,90,96,101,104,117,140],"each":[75],"aspect":[76],"document.":[79],"By":[80],"introducing":[81],"latent":[83],"variable,":[84],"i.e.,":[85],"polarity,":[88],"function,":[92],"inject":[95],"via":[103],"lower":[106,118],"bound.":[107,119],"We":[108,120],"optimizing":[116],"show":[121],"that":[122],"method":[124,143],"outperform":[126],"baselines":[129],"on":[130],"TripAdvisor":[131],"BeerAdvocate":[133],"datasets":[134],"comparable":[138],"state-of-the-art":[141],"with":[144],"hundreds":[145],"labels":[147],"per":[148],"aspect.":[149],"\u00a9":[150],"2019":[151],"Association":[152],"for":[153],"Computational":[154],"Linguistics":[155]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":5}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}