{"id":"https://openalex.org/W4399418584","doi":"https://doi.org/10.1145/3651671.3651725","title":"Chinese Named Entity Recognition in the Ship News Field Based on Adversarial Transfer Learning","display_name":"Chinese Named Entity Recognition in the Ship News Field Based on Adversarial Transfer Learning","publication_year":2024,"publication_date":"2024-02-02","ids":{"openalex":"https://openalex.org/W4399418584","doi":"https://doi.org/10.1145/3651671.3651725"},"language":"en","primary_location":{"id":"doi:10.1145/3651671.3651725","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3651671.3651725","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 16th International Conference on Machine Learning and Computing","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/A5044865400","display_name":"Zhihong Zhu","orcid":"https://orcid.org/0009-0007-8954-6737"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhihong Zhu","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101643168","display_name":"Weiwen Zhang","orcid":"https://orcid.org/0000-0002-5098-6459"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwen Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087419349","display_name":"Hongbin Zhang","orcid":"https://orcid.org/0000-0001-6568-5117"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongbin Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032362514","display_name":"Lianglun Cheng","orcid":"https://orcid.org/0000-0002-8213-041X"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianglun Cheng","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology, China","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5044865400"],"corresponding_institution_ids":["https://openalex.org/I139024713"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06346162,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"562","last_page":"567"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9991000294685364,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9508000016212463,"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/named-entity-recognition","display_name":"Named-entity recognition","score":0.9053645730018616},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.8902186155319214},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8629817962646484},{"id":"https://openalex.org/keywords/sequence-labeling","display_name":"Sequence labeling","score":0.8246911764144897},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7328178286552429},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7296682596206665},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6318749785423279},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.600780725479126},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5829358100891113},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5823437571525574},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5610541701316833},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5080139636993408},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4530985355377197},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.42424729466438293},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.4208940863609314},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.392245888710022}],"concepts":[{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.9053645730018616},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.8902186155319214},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8629817962646484},{"id":"https://openalex.org/C35639132","wikidata":"https://www.wikidata.org/wiki/Q7452468","display_name":"Sequence labeling","level":3,"score":0.8246911764144897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7328178286552429},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7296682596206665},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6318749785423279},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.600780725479126},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5829358100891113},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5823437571525574},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5610541701316833},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5080139636993408},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4530985355377197},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.42424729466438293},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.4208940863609314},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.392245888710022},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3651671.3651725","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3651671.3651725","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 16th International Conference on Machine Learning and Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2890459330","https://openalex.org/W2892181857","https://openalex.org/W2952112859","https://openalex.org/W2962904552","https://openalex.org/W2963326042","https://openalex.org/W2963338481","https://openalex.org/W2966070016","https://openalex.org/W3034379414","https://openalex.org/W3035642486","https://openalex.org/W3045965787","https://openalex.org/W3140899690","https://openalex.org/W4297802394"],"related_works":["https://openalex.org/W2962906565","https://openalex.org/W2798423868","https://openalex.org/W189110383","https://openalex.org/W3047727388","https://openalex.org/W2132038179","https://openalex.org/W2961904766","https://openalex.org/W2165958952","https://openalex.org/W2027233318","https://openalex.org/W2062502130","https://openalex.org/W3189432386"],"abstract_inverted_index":{"In":[0,70,97],"natural":[1],"language":[2],"processing":[3],"(NLP),":[4],"named":[5,20],"entity":[6],"recognition":[7],"(NER)":[8],"is":[9,84,112],"a":[10,23,75],"preliminary":[11],"task":[12,66,104,108],"that":[13],"aims":[14],"to":[15,114,158],"recognize":[16],"predefined":[17],"types":[18],"of":[19,29,58,86,118,126],"entities":[21],"from":[22,109],"given":[24],"text":[25],"sequence.":[26],"The":[27],"accuracy":[28,117],"NER":[30,65,77,107,119],"has":[31],"been":[32],"significantly":[33],"increased":[34],"by":[35],"deep":[36,39],"learning.":[37],"However,":[38],"learning":[40,130],"models":[41],"rely":[42],"heavily":[43],"on":[44,80,143,151],"annotated":[45,60],"data":[46],"while":[47],"many":[48],"specific":[49],"fields,":[50],"e.g.,":[51],"the":[52,64,99,106,116,121,124,159,164,172],"ship":[53,154,173],"news":[54,155,174],"field,":[55],"often":[56],"lack":[57],"extensive":[59],"data,":[61],"which":[62,83],"makes":[63],"much":[67],"more":[68],"challenging.":[69],"this":[71],"paper,":[72],"we":[73],"propose":[74],"new":[76],"model":[78,162],"based":[79],"adversarial":[81],"learning,":[82],"composed":[85],"BERT,":[87],"convolutional":[88],"neural":[89],"networks":[90],"(CNN)":[91],"and":[92,136,167],"conditional":[93],"random":[94],"fields":[95],"(CRF).":[96],"addition,":[98],"Chinese":[100],"word":[101],"segmentation":[102],"(CWS)":[103],"or":[105],"different":[110,145],"domains":[111],"introduced":[113],"increase":[115],"in":[120,171],"domain":[122],"through":[123],"transfer":[125],"task-shared":[127,134],"information.":[128],"Adversarial":[129],"can":[131],"fully":[132],"exploit":[133],"information":[135],"filter":[137],"out":[138],"noise.":[139],"Experiments":[140],"are":[141],"conducted":[142],"three":[144],"public":[146],"datasets,":[147],"as":[148,150],"well":[149],"our":[152,161],"own":[153],"dataset.":[156],"According":[157],"results,":[160],"outperforms":[163],"state-of-the-art":[165],"baselines":[166],"achieves":[168],"good":[169],"performance":[170],"field.":[175]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
