{"id":"https://openalex.org/W3195952981","doi":"https://doi.org/10.1145/3469213.3470396","title":"Irony recognition combined with LDA and improved one-dimensional intra-attention model","display_name":"Irony recognition combined with LDA and improved one-dimensional intra-attention model","publication_year":2021,"publication_date":"2021-05-28","ids":{"openalex":"https://openalex.org/W3195952981","doi":"https://doi.org/10.1145/3469213.3470396","mag":"3195952981"},"language":"en","primary_location":{"id":"doi:10.1145/3469213.3470396","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469213.3470396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 2nd International Conference on Artificial Intelligence and Information Systems","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/A5101972409","display_name":"Kai Wen","orcid":"https://orcid.org/0000-0001-8420-7612"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Wen","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications and Research Center of New Telecommunication Technology Applications,Chongqing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications and Research Center of New Telecommunication Technology Applications,Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100637388","display_name":"Hanlin Wang","orcid":"https://orcid.org/0000-0003-3128-1055"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanlin Wang","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications and Research Center of New Telecommunication Technology Applications,Chongqing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications and Research Center of New Telecommunication Technology Applications,Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045020900","display_name":"Jiali Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiali Lu","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications and Research Center of New Telecommunication Technology Applications,Chongqing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications and Research Center of New Telecommunication Technology Applications,Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080960196","display_name":"Zhenkang Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenkang Zhang","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications and Research Center of New Telecommunication Technology Applications,Chongqing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications and Research Center of New Telecommunication Technology Applications,Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I10535382"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10582359,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9987000226974487,"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":0.9987000226974487,"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":0.9986000061035156,"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":0.996399998664856,"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/irony","display_name":"Irony","score":0.9000038504600525},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.8600437045097351},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7256945371627808},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6594807505607605},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5747183561325073},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5361018180847168},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5245147943496704},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.48799577355384827},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4877346456050873},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45564115047454834},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4240749180316925},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.21903866529464722},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1802312135696411}],"concepts":[{"id":"https://openalex.org/C2779975665","wikidata":"https://www.wikidata.org/wiki/Q131361","display_name":"Irony","level":2,"score":0.9000038504600525},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.8600437045097351},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7256945371627808},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6594807505607605},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5747183561325073},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5361018180847168},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5245147943496704},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.48799577355384827},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4877346456050873},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45564115047454834},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4240749180316925},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.21903866529464722},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1802312135696411},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3469213.3470396","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469213.3470396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 2nd International Conference on Artificial Intelligence and Information Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2321588627","https://openalex.org/W2593051978","https://openalex.org/W2604716683","https://openalex.org/W2962681323"],"related_works":["https://openalex.org/W2364733638","https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W4226420367","https://openalex.org/W2347915009","https://openalex.org/W2385899941","https://openalex.org/W2373895987","https://openalex.org/W2980176872","https://openalex.org/W2380817186","https://openalex.org/W4381430104"],"abstract_inverted_index":{"For":[0],"short":[1,74],"texts":[2],"with":[3,104],"ironic":[4,55],"emotions,":[5],"because":[6],"the":[7,22,40,43,49,60,63,68,73,78,83,88,92,95,118],"data":[8,121,125],"is":[9,37],"sparse":[10],"and":[11,18,76,123],"irony":[12,27,34,106],"features":[13],"are":[14,98],"difficult":[15],"to":[16,66,81],"predict":[17],"extract,":[19],"which":[20],"causes":[21],"problem":[23],"of":[24,26,42,54,72,87],"substitution":[25],"text":[28,75],"recognition":[29,35,107],"accuracy,":[30],"a":[31],"more":[32],"accurate":[33],"model":[36,65,80],"proposed.":[38],"On":[39],"basis":[41],"internal":[44],"attention":[45],"model,":[46],"focus":[47],"on":[48,117],"unique":[50],"contradictory":[51],"emotional":[52],"vocabulary":[53],"sentences;":[56],"then,":[57],"simultaneously":[58],"input":[59],"sentences":[61],"into":[62],"LDA":[64],"obtain":[67,82],"maximum":[69],"probability":[70],"topic":[71],"use":[77],"Bi-LSTM":[79],"two-way":[84],"semantic":[85],"dependence":[86],"text;":[89],"Finally,":[90],"before":[91],"prediction":[93],"layer,":[94],"above":[96],"three":[97],"spliced":[99],"for":[100],"softmax":[101],"classification.":[102],"Compared":[103],"traditional":[105],"models":[108],"such":[109],"as":[110],"LSTM,":[111],"it":[112],"has":[113],"achieved":[114],"better":[115],"results":[116],"Weibo":[119],"comment":[120],"set":[122],"Ptacek":[124],"set.":[126]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}