{"id":"https://openalex.org/W3159927234","doi":"https://doi.org/10.3233/jifs-210440","title":"MF-COTE: A chinese opinion target extraction model based on multiple features","display_name":"MF-COTE: A chinese opinion target extraction model based on multiple features","publication_year":2021,"publication_date":"2021-05-05","ids":{"openalex":"https://openalex.org/W3159927234","doi":"https://doi.org/10.3233/jifs-210440","mag":"3159927234"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-210440","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-210440","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-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/A5001448144","display_name":"Xingyue Dang","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingyue Dang","raw_affiliation_strings":["School of Cyber Science and Engineering, Sichuan University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102791938","display_name":"Shan Liao","orcid":"https://orcid.org/0000-0002-9271-7695"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Liao","raw_affiliation_strings":["School of Cyber Science and Engineering, Sichuan University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019916687","display_name":"Pengsen Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengsen Cheng","raw_affiliation_strings":["School of Cyber Science and Engineering, Sichuan University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101869351","display_name":"Jiayong Liu","orcid":"https://orcid.org/0000-0003-3021-3771"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiayong Liu","raw_affiliation_strings":["School of Cyber Science and Engineering, Sichuan University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101869351"],"corresponding_institution_ids":["https://openalex.org/I24185976"],"apc_list":null,"apc_paid":null,"fwci":0.136,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.52035999,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"41","issue":"1","first_page":"1611","last_page":"1626"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9977999925613403,"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":0.9975000023841858,"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":0.8399173021316528},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.7536853551864624},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6346401572227478},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6154729723930359},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5932332873344421},{"id":"https://openalex.org/keywords/crfs","display_name":"CRFS","score":0.504355788230896},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4843645989894867},{"id":"https://openalex.org/keywords/noun","display_name":"Noun","score":0.4743427336215973},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.44093844294548035},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.42684507369995117},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.42540380358695984},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.38801705837249756}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8399173021316528},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.7536853551864624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6346401572227478},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6154729723930359},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5932332873344421},{"id":"https://openalex.org/C2775953691","wikidata":"https://www.wikidata.org/wiki/Q5013874","display_name":"CRFS","level":3,"score":0.504355788230896},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4843645989894867},{"id":"https://openalex.org/C121934690","wikidata":"https://www.wikidata.org/wiki/Q1084","display_name":"Noun","level":2,"score":0.4743427336215973},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.44093844294548035},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.42684507369995117},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.42540380358695984},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.38801705837249756},{"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-210440","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-210440","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W156016533","https://openalex.org/W1966331708","https://openalex.org/W2030439497","https://openalex.org/W2064675550","https://openalex.org/W2106325637","https://openalex.org/W2159457224","https://openalex.org/W2185993641","https://openalex.org/W2186926265","https://openalex.org/W2335163676","https://openalex.org/W2393262577","https://openalex.org/W2427312199","https://openalex.org/W2594568452","https://openalex.org/W2604205681","https://openalex.org/W2756381707","https://openalex.org/W2897533644","https://openalex.org/W2984191341","https://openalex.org/W3043102860","https://openalex.org/W3083435909","https://openalex.org/W3128916430","https://openalex.org/W6606418624"],"related_works":["https://openalex.org/W2356597680","https://openalex.org/W50079190","https://openalex.org/W182104056","https://openalex.org/W2111726165","https://openalex.org/W2011251309","https://openalex.org/W2511246383","https://openalex.org/W3108423214","https://openalex.org/W2796133761","https://openalex.org/W3088215229","https://openalex.org/W2184553228"],"abstract_inverted_index":{"Recently,":[0],"deep":[1],"learning":[2],"methods":[3],"have":[4],"been":[5],"applied":[6],"to":[7,159,170,187,209],"deal":[8],"with":[9,16,224,229],"the":[10,20,24,28,45,49,56,62,74,79,84,91,95,106,131,161,167,172,189,193,196,211,214,230,237,239,242],"opinion":[11,146,205],"target":[12,147,206],"extraction":[13,108,148],"(OTE)":[14],"task":[15,58],"fruitful":[17],"achievements.":[18],"On":[19],"other":[21,225],"hand,":[22],"since":[23],"features":[25,122,155,165],"captured":[26],"by":[27],"embedding":[29,40],"layer":[30,41],"can":[31,43,60,153],"make":[32],"a":[33,37,67,117,203],"multiple-perspective":[34],"analysis":[35],"from":[36,127,156],"sentence,":[38,180],"an":[39],"that":[42],"grasp":[44],"high-level":[46],"semantics":[47],"of":[48,52,64,73,97,133,166,175,213,232],"sentences":[50],"is":[51],"essence":[53],"for":[54,94,144],"processing":[55],"OTE":[57],"and":[59,123,139,163,241],"improve":[61],"performance":[63,100],"model":[65,118,190],"into":[66],"more":[68],"efficient":[69],"manner.":[70],"However,":[71],"most":[72],"existing":[75,226],"studies":[76],"focused":[77],"on":[78,130,192,236],"network":[80],"structure":[81],"rather":[82],"than":[83],"significant":[85],"embedded":[86],"layer,":[87],"which":[88,152],"may":[89],"be":[90],"fundamental":[92],"reason":[93],"problem":[96],"relatively":[98],"poor":[99],"in":[101,178],"this":[102,114],"field,":[103],"not":[104],"mention":[105],"Chinese":[107,145],"model.":[109],"To":[110],"compensate":[111],"these":[112],"shortcomings,":[113],"paper":[115],"proposes":[116],"using":[119],"multiple":[120,176],"effective":[121],"Bidirectional":[124,134],"Encoder":[125],"Representations":[126],"Transformers":[128],"(BERT)":[129],"architecture":[132],"Long":[135],"Short-Term":[136],"Memory":[137],"(BiLSTM)":[138],"Conditional":[140],"Random":[141],"Field":[142],"(CRF)":[143],"task,":[149],"namely":[150],"MF-COTE,":[151],"construct":[154],"different":[157],"perspectives":[158],"capture":[160],"context":[162],"local":[164],"sentences.":[168],"Besides,":[169],"handle":[171],"difficult":[173],"case":[174],"nouns":[177],"one":[179],"we":[181],"innovatively":[182],"propose":[183],"noting":[184],"words":[185],"feature":[186],"regulate":[188],"emphasize":[191],"noun":[194],"near":[195],"transition":[197],"or":[198],"contrast":[199],"word,":[200],"thus":[201],"leading":[202],"better":[204],"location.":[207],"Moreover,":[208],"demonstrate":[210],"superiorities":[212],"proposed":[215],"model,":[216],"extensive":[217],"comparison":[218],"experiments":[219],"are":[220],"systematically":[221],"conducted":[222],"compared":[223],"state-of-the-art":[227],"methods,":[228],"F1-score":[231],"90.76%,":[233],"92.10%,":[234],"89.63%":[235],"Baidu,":[238],"Dianping,":[240],"Mafengwo":[243],"dataset,":[244],"respectively.":[245]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}