{"id":"https://openalex.org/W3210227704","doi":"https://doi.org/10.1109/itsc48978.2021.9565087","title":"Adversarial training for named entity recognition of rail fault text","display_name":"Adversarial training for named entity recognition of rail fault text","publication_year":2021,"publication_date":"2021-09-19","ids":{"openalex":"https://openalex.org/W3210227704","doi":"https://doi.org/10.1109/itsc48978.2021.9565087","mag":"3210227704"},"language":"en","primary_location":{"id":"doi:10.1109/itsc48978.2021.9565087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc48978.2021.9565087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Intelligent Transportation Systems Conference (ITSC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5067097302","display_name":"Jiantao Qu","orcid":"https://orcid.org/0000-0002-8664-2236"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"J. Qu","raw_affiliation_strings":["State Key Laboratory of Traffic Control and Safety, Beijing Jiaotong University, Beijing, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Traffic Control and Safety, Beijing Jiaotong University, Beijing, P. R. China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038996257","display_name":"Shuai Su","orcid":"https://orcid.org/0000-0001-8412-9853"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"S. Su","raw_affiliation_strings":["Frontiers Science Center for Smart High-speed Railway System, Beijinz Jiaotong University, Beijing, P. R. China","State Key Laboratory of Traffic Control and Safety, Beijing Jiaotong University, Beijing, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Frontiers Science Center for Smart High-speed Railway System, Beijinz Jiaotong University, Beijing, P. R. China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"State Key Laboratory of Traffic Control and Safety, Beijing Jiaotong University, Beijing, P. R. China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103127011","display_name":"Runmei Li","orcid":"https://orcid.org/0000-0002-9034-1399"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"R. Li","raw_affiliation_strings":["State Key Laboratory of Traffic Control and Safety, Beijing Jiaotong University, Beijing, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Traffic Control and Safety, Beijing Jiaotong University, Beijing, P. R. China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036663288","display_name":"G. Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"G. Wang","raw_affiliation_strings":["Rutgers University, Piscataway, New Jersey, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University, Piscataway, New Jersey, USA","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1353","last_page":"1358"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9965000152587891,"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":0.9965000152587891,"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":0.996399998664856,"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":0.8047214150428772},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.7761428356170654},{"id":"https://openalex.org/keywords/named-entity-recognition","display_name":"Named-entity recognition","score":0.7730550765991211},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7488840818405151},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6823027729988098},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5977108478546143},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.583278238773346},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5731726884841919},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5338861346244812},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5194203853607178},{"id":"https://openalex.org/keywords/text-segmentation","display_name":"Text segmentation","score":0.5099083185195923},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4950474798679352},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4919681251049042},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4896140694618225},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.48034942150115967},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46619147062301636},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4502234160900116},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3978351652622223},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3232121467590332},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12406894564628601},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.08196219801902771},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.08005136251449585}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8047214150428772},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.7761428356170654},{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.7730550765991211},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7488840818405151},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6823027729988098},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5977108478546143},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.583278238773346},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5731726884841919},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5338861346244812},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5194203853607178},{"id":"https://openalex.org/C98501671","wikidata":"https://www.wikidata.org/wiki/Q1948408","display_name":"Text segmentation","level":3,"score":0.5099083185195923},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4950474798679352},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4919681251049042},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4896140694618225},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.48034942150115967},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46619147062301636},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4502234160900116},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3978351652622223},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3232121467590332},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12406894564628601},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.08196219801902771},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.08005136251449585},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"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/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc48978.2021.9565087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc48978.2021.9565087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Intelligent Transportation Systems Conference (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7099999785423279}],"awards":[{"id":"https://openalex.org/G1430188453","display_name":null,"funder_award_id":"SQ2020YFB160702","funder_id":"https://openalex.org/F4320323067","funder_display_name":"State Key Laboratory of Rail Traffic Control and Safety"},{"id":"https://openalex.org/G3328054620","display_name":null,"funder_award_id":"SQ2020YFB160702","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320323067","display_name":"State Key Laboratory of Rail Traffic Control and Safety","ror":"https://ror.org/01yj56c84"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W173870552","https://openalex.org/W1614298861","https://openalex.org/W1810943226","https://openalex.org/W1940872118","https://openalex.org/W1967350923","https://openalex.org/W2147880316","https://openalex.org/W2163918411","https://openalex.org/W2287139952","https://openalex.org/W2517194566","https://openalex.org/W2890459330","https://openalex.org/W2945000172","https://openalex.org/W2946448530","https://openalex.org/W2950577311","https://openalex.org/W2951290378","https://openalex.org/W2973376554","https://openalex.org/W2976327234","https://openalex.org/W2991635565","https://openalex.org/W3011594683","https://openalex.org/W3134035453","https://openalex.org/W3139957115","https://openalex.org/W3159843711","https://openalex.org/W3159954685","https://openalex.org/W3173493645","https://openalex.org/W3179145845","https://openalex.org/W6638273328","https://openalex.org/W6640362995","https://openalex.org/W6682082992"],"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/W2061834489","https://openalex.org/W2751906762","https://openalex.org/W3088215229","https://openalex.org/W2078793151","https://openalex.org/W3047727388"],"abstract_inverted_index":{"At":[0,90],"present,":[1],"most":[2],"rail":[3,149,179],"faults":[4,49],"in":[5,10,26,147,177],"metro":[6],"systems":[7],"are":[8,45,145],"recorded":[9],"the":[11,17,27,72,91,94,107,121,127,132,137,148,155,160,167,171,178],"form":[12],"of":[13,19,112,120],"text.":[14],"Due":[15],"to":[16,47,65,102,116,169],"lack":[18],"effective":[20],"mining":[21],"and":[22,40,50,124],"analysis":[23,176],"tools,":[24],"information":[25,123],"massive":[28],"textual":[29,174],"data":[30,175],"is":[31,63,77,100,115],"not":[32],"fully":[33],"utilized.":[34],"Learning":[35],"from":[36],"past":[37],"fault":[38,143],"texts":[39],"identifying":[41],"some":[42],"key":[43],"concepts":[44],"essential":[46],"analyze":[48],"help":[51],"decision":[52],"making.":[53],"In":[54,69],"this":[55,67,70],"paper,":[56],"a":[57],"word-enhanced":[58],"adversarial":[59,104,113],"training":[60,105,114],"model":[61,156],"(AT-BiLSTM-CRF)":[62],"proposed":[64],"address":[66],"problem.":[68],"model,":[71],"named":[73],"entity":[74],"recognition":[75],"(NER)":[76],"achieved":[78],"by":[79,130],"bi-directional":[80],"long":[81],"short-term":[82],"memory":[83],"(BiLSTM)":[84],"with":[85,106],"conditional":[86],"random":[87],"field":[88],"(CRF).":[89],"same":[92],"time,":[93],"Chinese":[95],"word":[96],"segmentation":[97],"(CWS)":[98],"task":[99],"introduced":[101],"conduct":[103],"NER":[108],"task.":[109,134],"The":[110,151],"structure":[111],"make":[117],"full":[118],"use":[119],"boundary":[122],"filter":[125],"out":[126],"noise":[128],"caused":[129],"introducing":[131],"CWS":[133],"More":[135],"importantly,":[136],"experiments":[138],"on":[139],"five":[140],"different":[141],"train":[142],"datasets":[144],"conducted":[146],"field.":[150,180],"results":[152],"show":[153],"that":[154],"performs":[157],"better":[158],"than":[159],"state-of-the-art":[161],"baselines,":[162],"which":[163],"indicates":[164],"it":[165],"has":[166],"potential":[168],"lay":[170],"foundation":[172],"for":[173]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}