乐胖代购免代理版

{"id":"https://openalex.org/W1622600386","doi":"https://doi.org/10.1609/aaai.v29i1.9194","title":"Representation Learning for Aspect Category Detection in Online Reviews","display_name":"Representation Learning for Aspect Category Detection in Online Reviews","publication_year":2015,"publication_date":"2015-02-09","ids":{"openalex":"https://openalex.org/W1622600386","doi":"https://doi.org/10.1609/aaai.v29i1.9194","mag":"1622600386"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v29i1.9194","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/9194/9053","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/9194/9053","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015186396","display_name":"Xinjie Zhou","orcid":"https://orcid.org/0000-0003-0006-287X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinjie Zhou","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China and The MOE Key Laboratory of Computational Linguistics, Peking University, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China and The MOE Key Laboratory of Computational Linguistics, Peking University, Beijing, China#TAB#","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029568096","display_name":"Xiaojun Wan","orcid":"https://orcid.org/0000-0001-6887-1994"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojun Wan","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China and The MOE Key Laboratory of Computational Linguistics, Peking University, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China and The MOE Key Laboratory of Computational Linguistics, Peking University, Beijing, China#TAB#","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100861201","display_name":"Jianguo Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianguo Xiao","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China and The MOE Key Laboratory of Computational Linguistics, Peking University, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China and The MOE Key Laboratory of Computational Linguistics, Peking University, Beijing, China#TAB#","institution_ids":["https://openalex.org/I20231570"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.362,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":106,"citation_normalized_percentile":{"value":0.950381,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"29","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9999,"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":0.9999,"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":0.9971,"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":0.9944,"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/word-embedding","display_name":"Word embedding","score":0.6774427},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature Engineering","score":0.5424214},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment Analysis","score":0.52821994},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.52123415},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature Learning","score":0.4751087},{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.46270397}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.80852973},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.6774427},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.65628964},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5667893},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5578907},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.5424214},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.52821994},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.52123415},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4751087},{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.46270397},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.4384238},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4193342},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41702548},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.41056657},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.37778074},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26979414},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v29i1.9194","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/9194/9053","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v29i1.9194","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/9194/9053","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"score":0.56,"display_name":"Peace, justice, and strong institutions","id":"https://metadata.un.org/sdg/16"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":30,"referenced_works":["https://openalex.org/W100623710","https://openalex.org/W104683736","https://openalex.org/W1544805753","https://openalex.org/W2001259128","https://openalex.org/W2096110600","https://openalex.org/W2097752345","https://openalex.org/W2103305545","https://openalex.org/W2106477703","https://openalex.org/W2117130368","https://openalex.org/W2120861206","https://openalex.org/W2128507180","https://openalex.org/W2129604374","https://openalex.org/W2131462252","https://openalex.org/W2138204974","https://openalex.org/W2153579005","https://openalex.org/W2158139315","https://openalex.org/W2159457224","https://openalex.org/W2160660844","https://openalex.org/W2164019165","https://openalex.org/W2166706824","https://openalex.org/W2250539671","https://openalex.org/W2250717533","https://openalex.org/W2250879510","https://openalex.org/W2251648804","https://openalex.org/W2251770468","https://openalex.org/W2252057809","https://openalex.org/W3146306708","https://openalex.org/W319996907","https://openalex.org/W4233906699","https://openalex.org/W4294170691"],"related_works":["https://openalex.org/W4308088897","https://openalex.org/W4200618314","https://openalex.org/W3186997021","https://openalex.org/W2997097677","https://openalex.org/W2954439574","https://openalex.org/W2785740378","https://openalex.org/W2771357047","https://openalex.org/W2753242182","https://openalex.org/W2726375170","https://openalex.org/W2146338426"],"abstract_inverted_index":{"User-generated":[0],"reviews":[1,116],"are":[2,155],"valuable":[3],"resources":[4],"for":[5,93],"decision":[6],"making.":[7],"Identifying":[8],"the":[9,53,75,134,145,150,168,173],"aspect":[10,38,94,151],"categories":[11],"discussed":[12],"in":[13,22],"a":[14,36,48,84,98,112,159,180],"given":[15],"review":[16],"sentence":[17],"(e.g.,":[18],"\u201cfood\u201d":[19],"and":[20,32,47,70,126,171],"\u201cservice\u201d":[21],"restaurant":[23],"reviews)":[24],"is":[25,62,103,141],"an":[26],"important":[27],"task":[28],"of":[29,115],"sentiment":[30],"analysis":[31],"opinion":[33],"mining.":[34],"Given":[35],"predefined":[37],"category":[39,95],"set,":[40],"most":[41],"previous":[42],"researches":[43],"leverage":[44],"hand-crafted":[45],"features":[46,92,128,147],"classification":[49],"algorithm":[50,102],"to":[51,58,88,106,123,148],"accomplish":[52],"task.":[54],"The":[55,153],"crucial":[56],"step":[57],"achieve":[59],"better":[60],"performance":[61,170],"feature":[63],"engineering":[64],"which":[65],"consumes":[66],"much":[67],"human":[68],"effort":[69],"may":[71],"be":[72],"unstable":[73],"when":[74],"product":[76],"domain":[77],"changes.":[78],"In":[79],"this":[80],"paper,":[81],"we":[82,121],"propose":[83,122],"representation":[85],"learning":[86],"approach":[87,166],"automatically":[89],"learn":[90],"useful":[91],"detection.":[96],"Specifically,":[97],"semi-supervised":[99],"word":[100,109,135],"embedding":[101],"first":[104],"proposed":[105],"obtain":[107],"continuous":[108],"representations":[110],"on":[111,133,158],"large":[113],"set":[114],"with":[117,144],"noisy":[118],"labels.":[119],"Afterwards,":[120],"generate":[124],"deeper":[125],"hybrid":[127,146],"through":[129],"neural":[130],"networks":[131],"stacked":[132],"vectors.":[136],"A":[137],"logistic":[138],"regression":[139],"classifier":[140],"finally":[142],"trained":[143],"predict":[149],"category.":[152],"experiments":[154],"carried":[156],"out":[157],"benchmark":[160],"dataset":[161],"released":[162],"by":[163],"SemEval-2014.":[164],"Our":[165],"achieves":[167],"state-of-the-art":[169],"outperforms":[172],"best":[174],"participating":[175],"team":[176],"as":[177,179],"well":[178],"few":[181],"strong":[182],"baselines.":[183]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W1622600386","counts_by_year":[{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":28},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":13}],"updated_date":"2025-01-16T15:10:23.223605","created_date":"2016-06-24"}