{"id":"https://openalex.org/W2554720547","doi":"https://doi.org/10.1109/ijcnn.2016.7727384","title":"Sentiment classification using Comprehensive Attention Recurrent models","display_name":"Sentiment classification using Comprehensive Attention Recurrent models","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2554720547","doi":"https://doi.org/10.1109/ijcnn.2016.7727384","mag":"2554720547"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2016.7727384","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727384","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5100419834","display_name":"Yong Zhang","orcid":"https://orcid.org/0000-0003-0066-3448"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Yong Zhang","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100535634","display_name":"Joo Er Meng","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Joo Er Meng","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore, SG"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore, SG","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100768898","display_name":"Rajasekar Venkatesan","orcid":"https://orcid.org/0000-0002-4061-7801"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Rajasekar Venkatesan","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058107332","display_name":"Ning Wang","orcid":"https://orcid.org/0000-0003-1745-1425"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Wang","raw_affiliation_strings":["Marine Engineering College, Dalian Maritime University, Dalian, China"],"affiliations":[{"raw_affiliation_string":"Marine Engineering College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036928886","display_name":"Mahardhika Pratama","orcid":"https://orcid.org/0000-0001-6531-5087"},"institutions":[{"id":"https://openalex.org/I196829312","display_name":"La Trobe University","ror":"https://ror.org/01rxfrp27","country_code":"AU","type":"education","lineage":["https://openalex.org/I196829312"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Mahardhika Pratama","raw_affiliation_strings":["Department of Computer Science and IT, La Trobe university, Melbourne, Victoria, Australia"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and IT, La Trobe university, Melbourne, Victoria, Australia","institution_ids":["https://openalex.org/I196829312"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100419834"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":9.4265,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.97988703,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1562","last_page":"1569"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9994999766349792,"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":0.9962000250816345,"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/recurrent-neural-network","display_name":"Recurrent neural network","score":0.939637303352356},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8303728103637695},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.672817051410675},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5972282886505127},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5681029558181763},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5139191150665283},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4454699456691742},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4450075328350067},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.4356956481933594},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.4345273971557617},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4273773431777954},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3928435146808624},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3091394305229187}],"concepts":[{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.939637303352356},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8303728103637695},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.672817051410675},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5972282886505127},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5681029558181763},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5139191150665283},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4454699456691742},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4450075328350067},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.4356956481933594},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.4345273971557617},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4273773431777954},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3928435146808624},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3091394305229187},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2016.7727384","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727384","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7099999785423279,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":77,"referenced_works":["https://openalex.org/W100623710","https://openalex.org/W142730124","https://openalex.org/W196214544","https://openalex.org/W1506229096","https://openalex.org/W1526096287","https://openalex.org/W1546771929","https://openalex.org/W1581407678","https://openalex.org/W1606347560","https://openalex.org/W1614298861","https://openalex.org/W1664573881","https://openalex.org/W1810943226","https://openalex.org/W1832693441","https://openalex.org/W1922658220","https://openalex.org/W1924770834","https://openalex.org/W1934184906","https://openalex.org/W1947481528","https://openalex.org/W1993882792","https://openalex.org/W1995436378","https://openalex.org/W2058580716","https://openalex.org/W2064675550","https://openalex.org/W2079735306","https://openalex.org/W2112796928","https://openalex.org/W2113459411","https://openalex.org/W2114524997","https://openalex.org/W2120615054","https://openalex.org/W2130942839","https://openalex.org/W2131462252","https://openalex.org/W2131744502","https://openalex.org/W2131774270","https://openalex.org/W2153579005","https://openalex.org/W2157331557","https://openalex.org/W2158139315","https://openalex.org/W2158899491","https://openalex.org/W2163683764","https://openalex.org/W2166706824","https://openalex.org/W2238685012","https://openalex.org/W2250489405","https://openalex.org/W2250521169","https://openalex.org/W2250966211","https://openalex.org/W2251143283","https://openalex.org/W2251939518","https://openalex.org/W2265846598","https://openalex.org/W2326377633","https://openalex.org/W2334209988","https://openalex.org/W2919115771","https://openalex.org/W2949547296","https://openalex.org/W2950577311","https://openalex.org/W2952230511","https://openalex.org/W2963921497","https://openalex.org/W2998704965","https://openalex.org/W4285719527","https://openalex.org/W4294170691","https://openalex.org/W4300336863","https://openalex.org/W6605727216","https://openalex.org/W6607974698","https://openalex.org/W6630206152","https://openalex.org/W6631369687","https://openalex.org/W6634906388","https://openalex.org/W6636358008","https://openalex.org/W6636510571","https://openalex.org/W6637116368","https://openalex.org/W6638273328","https://openalex.org/W6638834111","https://openalex.org/W6640212811","https://openalex.org/W6640617836","https://openalex.org/W6676984168","https://openalex.org/W6679224782","https://openalex.org/W6679436768","https://openalex.org/W6679775712","https://openalex.org/W6680532216","https://openalex.org/W6682691769","https://openalex.org/W6683557909","https://openalex.org/W6683738474","https://openalex.org/W6691459498","https://openalex.org/W6691642504","https://openalex.org/W6691723933","https://openalex.org/W6764062975"],"related_works":["https://openalex.org/W2329500892","https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W28991112","https://openalex.org/W2160451571","https://openalex.org/W2495256954","https://openalex.org/W2259317772"],"abstract_inverted_index":{"Sentiment":[0],"classification":[1,34,182],"has":[2],"been":[3],"a":[4,26,49,54,76,96],"very":[5,155],"hot":[6],"topic":[7],"in":[8,18,75],"the":[9,33,45,90,129,132,139,181,186,191,200],"field":[10],"of":[11,36,48,72,131,138],"natural":[12],"language":[13],"processing":[14],"(NLP)":[15],"and":[16,69,92,122,167,190],"understanding":[17],"recent":[19],"years.":[20],"Recurrent":[21,60],"neural":[22,83],"networks":[23,84],"(RNN)":[24],"is":[25,78,86,99,108,142,154],"widely":[27],"used":[28,87],"tool":[29],"to":[30,88,101,127,157],"deal":[31],"with":[32,185,199],"problem":[35],"variable-length":[37],"sentences.":[38],"The":[39,80,105],"standard":[40,106,187],"RNN":[41,107,115],"can":[42,65,145,178,194],"only":[43],"access":[44,89],"preceding":[46],"context":[47],"sentence.":[50],"In":[51],"this":[52],"paper,":[53],"new":[55,133,192],"architecture":[56],"termed":[57],"Comprehensive":[58],"Attention":[59],"Neural":[61],"Networks":[62],"(CA-RNN)":[63],"which":[64],"store":[66],"preceding,":[67],"succeeding":[68],"local":[70,103],"contexts":[71],"any":[73,150],"position":[74],"sequence":[77],"developed.":[79],"bidirectional":[81],"recurrent":[82,124,188],"(BRNN)":[85],"past":[91],"future":[93],"information":[94,177],"while":[95],"convolutional":[97],"layer":[98],"employed":[100],"capture":[102],"information.":[104],"also":[109],"replaced":[110],"by":[111],"two":[112],"recently":[113],"emerged":[114],"variants,":[116],"namely":[117],"long":[118],"short-term":[119],"memory":[120],"(LSTM)":[121],"gated":[123],"unit":[125],"(GRU),":[126],"enhance":[128,180],"effectiveness":[130],"architecture.":[134],"Another":[135],"salient":[136],"feature":[137],"proposed":[140],"model":[141],"that":[143,173],"it":[144],"be":[146,158],"trained":[147],"end-to-end":[148],"without":[149],"human":[151],"intervention.":[152],"It":[153],"easy":[156],"implemented.":[159],"We":[160],"conduct":[161],"experiments":[162],"on":[163],"several":[164],"sentiment-labeled":[165],"datasets":[166],"analysis":[168],"tasks.":[169],"Experiment":[170],"results":[171],"demonstrate":[172],"capturing":[174],"comprehensive":[175],"contextual":[176],"significantly":[179],"accuracy":[183],"compared":[184,198],"models":[189,193],"achieve":[195],"competitive":[196],"performance":[197],"state-of-the-art":[201],"approaches.":[202]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}