{"id":"https://openalex.org/W2988695847","doi":"https://doi.org/10.1109/icmlc48188.2019.8949286","title":"Multi-Channel Convolutional Neural Network for Targeted Sentiment Classification","display_name":"Multi-Channel Convolutional Neural Network for Targeted Sentiment Classification","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2988695847","doi":"https://doi.org/10.1109/icmlc48188.2019.8949286","mag":"2988695847"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc48188.2019.8949286","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc48188.2019.8949286","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Machine Learning and Cybernetics (ICMLC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101882265","display_name":"Ting Yuan","orcid":"https://orcid.org/0000-0002-0713-5974"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Yuan","raw_affiliation_strings":["South China Normal University,Guangzhou,China,510006","South China Normal University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China Normal University,Guangzhou,China,510006","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066956752","display_name":"Hai-Hui Li","orcid":null},"institutions":[{"id":"https://openalex.org/I182722699","display_name":"Shenzhen Polytechnic University","ror":"https://ror.org/00d2w9g53","country_code":"CN","type":"education","lineage":["https://openalex.org/I182722699"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai-Hui Li","raw_affiliation_strings":["Shenzhen Polytechnic,shenzhen,China,518055","Shenzhen Polytechnic, shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Polytechnic,shenzhen,China,518055","institution_ids":["https://openalex.org/I182722699"]},{"raw_affiliation_string":"Shenzhen Polytechnic, shenzhen, China","institution_ids":["https://openalex.org/I182722699"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055100812","display_name":"Hongya Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I182722699","display_name":"Shenzhen Polytechnic University","ror":"https://ror.org/00d2w9g53","country_code":"CN","type":"education","lineage":["https://openalex.org/I182722699"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong-Ya Zhao","raw_affiliation_strings":["Shenzhen Polytechnic,shenzhen,China,518055","Shenzhen Polytechnic, shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Polytechnic,shenzhen,China,518055","institution_ids":["https://openalex.org/I182722699"]},{"raw_affiliation_string":"Shenzhen Polytechnic, shenzhen, China","institution_ids":["https://openalex.org/I182722699"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100527280","display_name":"Qianhua Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian-Hua Cai","raw_affiliation_strings":["South China Normal University,Guangzhou,China,510006","South China Normal University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China Normal University,Guangzhou,China,510006","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100349055","display_name":"Han Liu","orcid":"https://orcid.org/0000-0002-7731-8258"},"institutions":[{"id":"https://openalex.org/I79510175","display_name":"Cardiff University","ror":"https://ror.org/03kk7td41","country_code":"GB","type":"education","lineage":["https://openalex.org/I79510175"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Han Liu","raw_affiliation_strings":["Cardiff University,Cardiff,United Kingdom,CF24 3AA","Cardiff University, Cardiff, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cardiff University,Cardiff,United Kingdom,CF24 3AA","institution_ids":["https://openalex.org/I79510175"]},{"raw_affiliation_string":"Cardiff University, Cardiff, United Kingdom","institution_ids":["https://openalex.org/I79510175"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100740224","display_name":"Xiaohui Hu","orcid":"https://orcid.org/0000-0001-5717-8676"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao-Hui Hu","raw_affiliation_strings":["South China Normal University,Guangzhou,China,510006","South China Normal University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China Normal University,Guangzhou,China,510006","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14597477,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2019","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9994000196456909,"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":0.9962999820709229,"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":0.8782822489738464},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.8018254041671753},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8016738891601562},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7305232882499695},{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.6981214284896851},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6414004564285278},{"id":"https://openalex.org/keywords/polarity","display_name":"Polarity (international relations)","score":0.5902796983718872},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5313390493392944},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.521206259727478},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4275706112384796},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34924182295799255}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8782822489738464},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.8018254041671753},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8016738891601562},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7305232882499695},{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.6981214284896851},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6414004564285278},{"id":"https://openalex.org/C2777361361","wikidata":"https://www.wikidata.org/wiki/Q1112585","display_name":"Polarity (international relations)","level":3,"score":0.5902796983718872},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5313390493392944},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.521206259727478},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4275706112384796},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34924182295799255},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C1491633281","wikidata":"https://www.wikidata.org/wiki/Q7868","display_name":"Cell","level":2,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icmlc48188.2019.8949286","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc48188.2019.8949286","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Machine Learning and Cybernetics (ICMLC)","raw_type":"proceedings-article"},{"id":"pmh:oai:https://orca.cardiff.ac.uk:124286","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401195","display_name":"ORCA Online Research @Cardiff (Cardiff University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79510175","host_organization_name":"Cardiff University","host_organization_lineage":["https://openalex.org/I79510175"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Conference or Workshop Item"},{"id":"mag:3084291233","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002240712796664","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5799999833106995}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W22861983","https://openalex.org/W1832693441","https://openalex.org/W2211192759","https://openalex.org/W2465978385","https://openalex.org/W2513378248","https://openalex.org/W2529550020","https://openalex.org/W2562607067","https://openalex.org/W2787654308","https://openalex.org/W2931941132","https://openalex.org/W2963428430","https://openalex.org/W3002830755","https://openalex.org/W6600949241","https://openalex.org/W6727807531"],"related_works":["https://openalex.org/W3116116498","https://openalex.org/W3029012650","https://openalex.org/W1988325893","https://openalex.org/W2776212826","https://openalex.org/W3214323197","https://openalex.org/W2805679416","https://openalex.org/W4385571001","https://openalex.org/W2805889480","https://openalex.org/W2117643817","https://openalex.org/W1984947604"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"targeted":[3,40],"sentiment":[4,13,17,41],"analysis":[5],"has":[6],"received":[7],"great":[8],"attention":[9],"as":[10],"a":[11,20,24,33,53],"fine-grained":[12],"analysis.":[14],"Determining":[15],"the":[16,27,50,89,94],"polarity":[18],"of":[19,52,96],"specific":[21],"target":[22],"in":[23],"sentence":[25,54],"is":[26],"main":[28],"task.":[29],"This":[30],"paper":[31],"proposes":[32],"multi-channel":[34],"convolutional":[35],"neural":[36],"network":[37],"(MCL-CNN)":[38],"for":[39],"classification.":[42],"Our":[43],"approach":[44],"can":[45,64,82],"not":[46],"only":[47],"parallelize":[48],"over":[49],"words":[51],"but":[55],"also":[56],"extract":[57],"local":[58],"features":[59,81],"effectively.":[60],"Contexts":[61],"and":[62,75],"targets":[63],"be":[65,83],"more":[66],"comprehensively":[67],"utilized":[68],"by":[69],"using":[70],"part-of-speech":[71],"information,":[72],"semantic":[73],"information":[74,77],"interactive":[76],"so":[78],"that":[79],"diverse":[80],"obtained.":[84],"Finally,":[85],"experimental":[86],"results":[87],"on":[88],"SemEval":[90],"2014":[91],"dataset":[92],"demonstrate":[93],"effectiveness":[95],"this":[97],"method.":[98]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
