{"id":"https://openalex.org/W2044432932","doi":"https://doi.org/10.1109/nlpke.2010.5587800","title":"Improving emotion recognition from text with fractionation training","display_name":"Improving emotion recognition from text with fractionation training","publication_year":2010,"publication_date":"2010-08-01","ids":{"openalex":"https://openalex.org/W2044432932","doi":"https://doi.org/10.1109/nlpke.2010.5587800","mag":"2044432932"},"language":"en","primary_location":{"id":"doi:10.1109/nlpke.2010.5587800","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nlpke.2010.5587800","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","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/A5100694806","display_name":"Ye Wu","orcid":"https://orcid.org/0000-0001-9038-2900"},"institutions":[{"id":"https://openalex.org/I922474255","display_name":"Tokushima University","ror":"https://ror.org/044vy1d05","country_code":"JP","type":"education","lineage":["https://openalex.org/I922474255"]},{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN","JP"],"is_corresponding":true,"raw_author_name":"Ye Wu","raw_affiliation_strings":["Faculty of Engineering, University of Tokushima, Tokushima, Japan","School of Computer, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Tokushima, Tokushima, Japan","institution_ids":["https://openalex.org/I922474255"]},{"raw_affiliation_string":"School of Computer, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071943346","display_name":"Fuji Ren","orcid":"https://orcid.org/0000-0003-4860-9184"},"institutions":[{"id":"https://openalex.org/I922474255","display_name":"Tokushima University","ror":"https://ror.org/044vy1d05","country_code":"JP","type":"education","lineage":["https://openalex.org/I922474255"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Fuji Ren","raw_affiliation_strings":["Faculty of Engineering, University of Tokushima, Tokushima, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Tokushima, Tokushima, Japan","institution_ids":["https://openalex.org/I922474255"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100694806"],"corresponding_institution_ids":["https://openalex.org/I139759216","https://openalex.org/I922474255"],"apc_list":null,"apc_paid":null,"fwci":0.451,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.72500121,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"8","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9993000030517578,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9993000030517578,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9991999864578247,"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":0.9979000091552734,"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/lexicon","display_name":"Lexicon","score":0.8432856798171997},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7893919944763184},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.7431722283363342},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.6913862228393555},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6477124691009521},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.588087260723114},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5693128108978271},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.5323958992958069},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.427762508392334},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4032413959503174},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32983362674713135}],"concepts":[{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.8432856798171997},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7893919944763184},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.7431722283363342},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.6913862228393555},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6477124691009521},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.588087260723114},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5693128108978271},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.5323958992958069},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.427762508392334},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4032413959503174},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32983362674713135},{"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:10.1109/nlpke.2010.5587800","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nlpke.2010.5587800","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W34176136","https://openalex.org/W180236776","https://openalex.org/W1977137834","https://openalex.org/W1989145535","https://openalex.org/W1996265292","https://openalex.org/W2095234413","https://openalex.org/W2097089247","https://openalex.org/W2106277949","https://openalex.org/W2114535528","https://openalex.org/W2125098710","https://openalex.org/W2132895695","https://openalex.org/W2134557008","https://openalex.org/W2149684865","https://openalex.org/W2150441399","https://openalex.org/W2153635508","https://openalex.org/W2165728620","https://openalex.org/W2166706824","https://openalex.org/W2172000360","https://openalex.org/W2339343773","https://openalex.org/W2435251607","https://openalex.org/W3120421331","https://openalex.org/W4230277160","https://openalex.org/W4285719527","https://openalex.org/W4294877277","https://openalex.org/W6607363741","https://openalex.org/W6678758578","https://openalex.org/W6679487084","https://openalex.org/W6682304300","https://openalex.org/W6717827561"],"related_works":["https://openalex.org/W2103942400","https://openalex.org/W2154970010","https://openalex.org/W1550318927","https://openalex.org/W4305042383","https://openalex.org/W2546649374","https://openalex.org/W2773396412","https://openalex.org/W4380854332","https://openalex.org/W2184859701","https://openalex.org/W4386232293","https://openalex.org/W4380370144"],"abstract_inverted_index":{"Previous":[0],"approaches":[1],"of":[2,39,95,102],"emotion":[3,22,32,53,77,84],"recognition":[4,54],"from":[5,23,80],"text":[6,24],"were":[7],"mostly":[8],"implemented":[9],"under":[10],"keyword-based":[11,16],"or":[12],"learning-based":[13],"frameworks.":[14],"However,":[15],"systems":[17],"are":[18],"unable":[19],"to":[20,86],"recognize":[21],"with":[25],"no":[26],"emotional":[27,44],"keywords,":[28],"and":[29,99],"constructing":[30],"an":[31,81],"lexicon":[33,78],"is":[34,73],"a":[35,69],"tough":[36],"work":[37],"because":[38],"ambiguity":[40],"in":[41],"defining":[42],"all":[43],"keywords.":[45],"Completely":[46],"prior-knowledge-free":[47],"supervised":[48],"machine":[49],"learning":[50],"methods":[51],"for":[52],"also":[55,107],"do":[56],"not":[57],"perform":[58],"as":[59,61],"well":[60],"on":[62],"some":[63,103],"traditional":[64],"tasks.":[65],"In":[66],"this":[67],"paper,":[68],"fractionation":[70],"training":[71],"approach":[72],"proposed,":[74],"utilizing":[75],"the":[76,93,96,100,109],"extracted":[79],"annotated":[82],"blog":[83],"corpus":[85],"train":[87],"SVM":[88],"classifiers.":[89],"Experimental":[90],"results":[91],"show":[92],"effectiveness":[94],"proposed":[97],"approach,":[98],"use":[101],"other":[104],"experimental":[105],"design":[106],"improves":[108],"classification":[110],"accuracy.":[111]},"counts_by_year":[{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}