{"id":"https://openalex.org/W2904376903","doi":"https://doi.org/10.1155/2018/1890683","title":"A Low-Cost Named Entity Recognition Research Based on Active Learning","display_name":"A Low-Cost Named Entity Recognition Research Based on Active Learning","publication_year":2018,"publication_date":"2018-12-18","ids":{"openalex":"https://openalex.org/W2904376903","doi":"https://doi.org/10.1155/2018/1890683","mag":"2904376903"},"language":"en","primary_location":{"id":"doi:10.1155/2018/1890683","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2018/1890683","pdf_url":"https://downloads.hindawi.com/journals/sp/2018/1890683.pdf","source":{"id":"https://openalex.org/S166774750","display_name":"Scientific Programming","issn_l":"1058-9244","issn":["1058-9244","1875-919X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Programming","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://downloads.hindawi.com/journals/sp/2018/1890683.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004151392","display_name":"Han Huang","orcid":"https://orcid.org/0000-0002-1517-9731"},"institutions":[{"id":"https://openalex.org/I158934434","display_name":"Zhongnan University of Economics and Law","ror":"https://ror.org/04yqxxq63","country_code":"CN","type":"education","lineage":["https://openalex.org/I158934434"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Huang","raw_affiliation_strings":["School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, China"],"raw_orcid":"https://orcid.org/0000-0002-1517-9731","affiliations":[{"raw_affiliation_string":"School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, China","institution_ids":["https://openalex.org/I158934434"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100422649","display_name":"Hongyu Wang","orcid":"https://orcid.org/0000-0002-5063-9166"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyu Wang","raw_affiliation_strings":["School of Information Management, Wuhan University, Wuhan 430072, China"],"raw_orcid":"https://orcid.org/0000-0002-5063-9166","affiliations":[{"raw_affiliation_string":"School of Information Management, Wuhan University, Wuhan 430072, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016193325","display_name":"Dawei Jin","orcid":"https://orcid.org/0000-0002-5922-2746"},"institutions":[{"id":"https://openalex.org/I158934434","display_name":"Zhongnan University of Economics and Law","ror":"https://ror.org/04yqxxq63","country_code":"CN","type":"education","lineage":["https://openalex.org/I158934434"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dawei Jin","raw_affiliation_strings":["School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, China"],"raw_orcid":"https://orcid.org/0000-0002-5922-2746","affiliations":[{"raw_affiliation_string":"School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, China","institution_ids":["https://openalex.org/I158934434"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5016193325"],"corresponding_institution_ids":["https://openalex.org/I158934434"],"apc_list":{"value":1800,"currency":"USD","value_usd":1800},"apc_paid":{"value":1800,"currency":"USD","value_usd":1800},"fwci":1.1843,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.84923768,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"2018","issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9898999929428101,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9837999939918518,"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/conditional-random-field","display_name":"Conditional random field","score":0.8596155643463135},{"id":"https://openalex.org/keywords/named-entity-recognition","display_name":"Named-entity recognition","score":0.7856895327568054},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.734137773513794},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6815754771232605},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6356189846992493},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5513262748718262},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4706510603427887},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.4669561982154846},{"id":"https://openalex.org/keywords/f1-score","display_name":"F1 score","score":0.45276984572410583},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4260895252227783},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3767673373222351},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3585171103477478}],"concepts":[{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.8596155643463135},{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.7856895327568054},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.734137773513794},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6815754771232605},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6356189846992493},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5513262748718262},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4706510603427887},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.4669561982154846},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.45276984572410583},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4260895252227783},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3767673373222351},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3585171103477478},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1155/2018/1890683","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2018/1890683","pdf_url":"https://downloads.hindawi.com/journals/sp/2018/1890683.pdf","source":{"id":"https://openalex.org/S166774750","display_name":"Scientific Programming","issn_l":"1058-9244","issn":["1058-9244","1875-919X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Programming","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2003033c307540b6b1015f9b0bf15d84","is_oa":false,"landing_page_url":"https://doaj.org/article/2003033c307540b6b1015f9b0bf15d84","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scientific Programming, Vol 2018 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2018/1890683","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2018/1890683","pdf_url":"https://downloads.hindawi.com/journals/sp/2018/1890683.pdf","source":{"id":"https://openalex.org/S166774750","display_name":"Scientific Programming","issn_l":"1058-9244","issn":["1058-9244","1875-919X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Programming","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G1373605983","display_name":null,"funder_award_id":"201811409","funder_id":"https://openalex.org/F4320310114","funder_display_name":"Zhongnan University of Economics and Law"}],"funders":[{"id":"https://openalex.org/F4320310114","display_name":"Zhongnan University of Economics and Law","ror":"https://ror.org/04yqxxq63"},{"id":"https://openalex.org/F4320337238","display_name":"Tr\u01b0\u1eddng \u0110\u1ea1i h\u1ecdc Kinh t\u1ebf - Lu\u1eadt, \u0110\u1ea1i h\u1ecdc Qu\u1ed1c gia Th\u00e0nh ph\u1ed1 H\u1ed3 Ch\u00ed Minh","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2904376903.pdf","grobid_xml":"https://content.openalex.org/works/W2904376903.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W2042051376","https://openalex.org/W2096623936","https://openalex.org/W2390918741","https://openalex.org/W2533179929","https://openalex.org/W2648561407","https://openalex.org/W2759824248","https://openalex.org/W2764083974","https://openalex.org/W2801320321","https://openalex.org/W2807800730","https://openalex.org/W2964154753","https://openalex.org/W3003930791","https://openalex.org/W4252861488"],"related_works":["https://openalex.org/W4250494529","https://openalex.org/W1964783010","https://openalex.org/W2399696375","https://openalex.org/W45206245","https://openalex.org/W2211396092","https://openalex.org/W11196620","https://openalex.org/W4305041692","https://openalex.org/W2078793151","https://openalex.org/W2061834489","https://openalex.org/W3201257042"],"abstract_inverted_index":{"Named":[0],"entity":[1],"recognition":[2,209],"(NER)":[3],"is":[4,38,58,74,132,138,155,169,227,242],"an":[5],"indispensable":[6],"and":[7,23,134,148,164,178,195,211,236,253],"very":[8],"important":[9],"part":[10],"of":[11,33,50,104,112,152,224],"many":[12],"natural":[13],"language":[14],"processing":[15],"technologies,":[16],"such":[17],"as":[18],"information":[19,21],"extraction,":[20],"retrieval,":[22],"intelligent":[24],"Q":[25],"&":[26],"A.":[27],"This":[28,245],"paper":[29],"describes":[30],"the":[31,34,51,55,59,62,67,77,91,102,105,110,118,125,129,135,142,149,153,159,165,185,216,221,238],"development":[32],"AL-CRF":[35,56,186],"model,":[36],"which":[37,86,108],"a":[39,249],"NER":[40,167,172],"approach":[41,226],"based":[42,140],"on":[43,76,141,176],"active":[44],"learning":[45,130,147],"(AL).":[46],"The":[47,98,146,188],"algorithmic":[48],"sequence":[49],"processes":[52],"performed":[53,75,175],"by":[54],"model":[57,168],"following:":[60],"first,":[61],"samples":[63,116],"are":[64,87,122,174],"clustered":[65],"using":[66],"k":[68],"-means":[69],"approach.":[70],"Then,":[71],"stratified":[72],"sampling":[73],"produced":[78],"clusters":[79],"in":[80,181,248],"order":[81,182],"to":[82,89,124,183,215],"obtain":[83],"initial":[84],"samples,":[85,235],"used":[88],"train":[90],"basic":[92],"conditional":[93],"random":[94],"field":[95],"(CRF)":[96],"classifier.":[97],"next":[99],"step":[100],"includes":[101],"initiation":[103],"selection":[106,150],"process":[107,131,151],"uses":[109],"criterion":[111],"entropy.":[113],"More":[114],"specifically,":[115],"having":[117],"highest":[119],"entropy":[120],"values":[121],"added":[123],"training":[126,144,234],"set.":[127,145],"Afterwards,":[128],"repeated,":[133],"CRF":[136,218],"classifier":[137],"retrained":[139],"obtained":[143],"AL":[154],"running":[156],"iteratively":[157],"until":[158],"harmonic":[160],"mean":[161],"F":[162],"stabilizes":[163],"final":[166],"obtained.":[170],"Several":[171],"experiments":[173],"legislative":[177],"medical":[179,198],"cases":[180],"validate":[184],"performance.":[187],"testing":[189],"data":[190],"include":[191],"Chinese":[192,196],"judicial":[193],"documents":[194],"electronic":[197],"records":[199],"(EMRs).":[200],"Testing":[201],"indicates":[202],"that":[203,228],"our":[204,225],"proposed":[205],"algorithm":[206],"has":[207],"better":[208],"accuracy":[210],"recall":[212],"rate":[213],"compared":[214],"conventional":[217],"model.":[219],"Moreover,":[220],"main":[222],"advantage":[223],"it":[229,241],"requires":[230],"fewer":[231],"manually":[232],"labelled":[233],"at":[237],"same":[239],"time,":[240],"more":[243,250,254],"effective.":[244],"can":[246],"result":[247],"cost":[251],"effective":[252],"reliable":[255],"process.":[256]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}