乐胖代购免代理版

{"id":"https://openalex.org/W1981256868","doi":"https://doi.org/10.1109/taslp.2015.2392381","title":"CLOpinionMiner: Opinion Target Extraction in a Cross-Language Scenario","display_name":"CLOpinionMiner: Opinion Target Extraction in a Cross-Language Scenario","publication_year":2015,"publication_date":"2015-01-14","ids":{"openalex":"https://openalex.org/W1981256868","doi":"https://doi.org/10.1109/taslp.2015.2392381","mag":"1981256868"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2015.2392381","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-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/A5101501384","display_name":"Xinjie Zhou","orcid":"https://orcid.org/0009-0002-9077-3180"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinjie Zhou","raw_affiliation_strings":["Institute of Computer Science and Technology, the MOE Key Laboratory of Computational Linguistics, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, the MOE Key Laboratory of Computational Linguistics, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029568096","display_name":"Xiaojun Wan","orcid":"https://orcid.org/0000-0001-6887-1994"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojun Wan","raw_affiliation_strings":["Institute of Computer Science and Technology, the MOE Key Laboratory of Computational Linguistics, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, the MOE Key Laboratory of Computational Linguistics, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100861201","display_name":"Jianguo Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianguo Xiao","raw_affiliation_strings":["Institute of Computer Science and Technology, the MOE Key Laboratory of Computational Linguistics, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, the MOE Key Laboratory of Computational Linguistics, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.177,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":19,"citation_normalized_percentile":{"value":0.953758,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":91},"biblio":{"volume":"23","issue":"4","first_page":"619","last_page":"630"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9999,"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":0.9999,"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":0.9991,"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":0.9971,"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/sentiment-analysis","display_name":"Sentiment Analysis","score":0.7117777},{"id":"https://openalex.org/keywords/sequence-labeling","display_name":"Sequence labeling","score":0.6790251},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5194237},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.45849076}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8259037},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.79285014},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7117777},{"id":"https://openalex.org/C35639132","wikidata":"https://www.wikidata.org/wiki/Q7452468","display_name":"Sequence labeling","level":3,"score":0.6790251},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6521964},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6057489},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.52988917},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5194237},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.45849076},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.42019665},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.07718828},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2015.2392381","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.79,"id":"https://metadata.un.org/sdg/4","display_name":"Quality education"}],"grants":[{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"61331011"},{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"61170166"}],"datasets":[],"versions":[],"referenced_works_count":42,"referenced_works":["https://openalex.org/W108081214","https://openalex.org/W1410460","https://openalex.org/W142730124","https://openalex.org/W1506674094","https://openalex.org/W1517771839","https://openalex.org/W1543039027","https://openalex.org/W1885010341","https://openalex.org/W1990903093","https://openalex.org/W2001064229","https://openalex.org/W2011450768","https://openalex.org/W2016630033","https://openalex.org/W2024226786","https://openalex.org/W2048679005","https://openalex.org/W2080656495","https://openalex.org/W2108287887","https://openalex.org/W2112508660","https://openalex.org/W2112544000","https://openalex.org/W2112744748","https://openalex.org/W2114524997","https://openalex.org/W2115834228","https://openalex.org/W2118045473","https://openalex.org/W2122455551","https://openalex.org/W2126183710","https://openalex.org/W2126581182","https://openalex.org/W2126854223","https://openalex.org/W2135731857","https://openalex.org/W2137207778","https://openalex.org/W2141891248","https://openalex.org/W2142262074","https://openalex.org/W2143995218","https://openalex.org/W2147880316","https://openalex.org/W2159457224","https://openalex.org/W2160660844","https://openalex.org/W2161228561","https://openalex.org/W2166706824","https://openalex.org/W2167660864","https://openalex.org/W2176820767","https://openalex.org/W2341078838","https://openalex.org/W2396458245","https://openalex.org/W2519011775","https://openalex.org/W4245504396","https://openalex.org/W4312789226"],"related_works":["https://openalex.org/W3136048405","https://openalex.org/W3126392069","https://openalex.org/W3027026357","https://openalex.org/W3015678144","https://openalex.org/W2996257819","https://openalex.org/W2962906565","https://openalex.org/W2944198262","https://openalex.org/W2798423868","https://openalex.org/W2109665237","https://openalex.org/W2076440176"],"abstract_inverted_index":{"Opinion":[0],"target":[1,56,88,93,104,127],"extraction":[2,57,89,128],"is":[3,10],"a":[4,24,48,70,83,91,141],"subtask":[5],"of":[6,44,149,168],"opinion":[7,55,87,103,126],"mining":[8],"which":[9,75],"very":[11],"useful":[12],"in":[13,38,47,58,82,90],"many":[14],"applications.":[15],"The":[16],"problem":[17],"has":[18],"usually":[19],"been":[20],"solved":[21],"by":[22,152],"training":[23,34,116],"sequence":[25],"labeler":[26],"on":[27,54,100,107,132,160],"manually":[28],"labeled":[29,33,45,80],"data.":[30],"However,":[31],"the":[32,42,51,65,78,108,147,154,161,166],"datasets":[35,117],"are":[36,129],"imbalanced":[37],"different":[39,92,119],"languages,":[40],"and":[41],"lack":[43],"corpus":[46],"language":[49,85],"limits":[50],"research":[52],"progress":[53],"this":[59,96],"language.":[60,94],"In":[61,95],"order":[62],"to":[63,145],"address":[64],"above":[66],"problem,":[67],"we":[68,98,139],"propose":[69],"novel":[71],"system":[72],"called":[73],"CLOpinionMiner":[74],"investigates":[76],"leveraging":[77,153],"rich":[79],"data":[81],"source":[84],"for":[86,124],"study,":[97],"focus":[99],"English-to-Chinese":[101],"cross-language":[102],"extraction.":[105],"Based":[106],"English":[109],"dataset,":[110],"our":[111,169],"method":[112],"produces":[113],"two":[114],"Chinese":[115,125,157],"with":[118],"features.":[120],"Two":[121],"labeling":[122],"models":[123,151],"trained":[130],"based":[131],"Conditional":[133],"Random":[134],"Fields":[135],"(CRF).":[136],"After":[137],"that,":[138],"use":[140],"monolingual":[142],"co-training":[143],"algorithm":[144],"improve":[146],"performance":[148],"both":[150],"enormous":[155],"unlabeled":[156],"review":[158],"texts":[159],"web.":[162],"Experimental":[163],"results":[164],"show":[165],"effectiveness":[167],"proposed":[170],"approach.":[171]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W1981256868","counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2024-12-29T17:23:21.678933","created_date":"2016-06-24"}