{"id":"https://openalex.org/W4380630265","doi":"https://doi.org/10.3233/jcm-226772","title":"A joint event extraction model based on RoBERTa-wwm-ext and gating mechanism","display_name":"A joint event extraction model based on RoBERTa-wwm-ext and gating mechanism","publication_year":2023,"publication_date":"2023-06-13","ids":{"openalex":"https://openalex.org/W4380630265","doi":"https://doi.org/10.3233/jcm-226772"},"language":"en","primary_location":{"id":"doi:10.3233/jcm-226772","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jcm-226772","pdf_url":null,"source":{"id":"https://openalex.org/S2765058733","display_name":"Journal of Computational Methods in Sciences and Engineering","issn_l":"1472-7978","issn":["1472-7978","1875-8983"],"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 Computational Methods in Sciences and Engineering","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/A5100562554","display_name":"Baosheng Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baosheng Yin","raw_affiliation_strings":["Research Center for Human-Computer Intelligence, Shenyang Aerospace University, Shenyang, Liaoning, China"],"affiliations":[{"raw_affiliation_string":"Research Center for Human-Computer Intelligence, Shenyang Aerospace University, Shenyang, Liaoning, China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100677198","display_name":"Hua Wu","orcid":"https://orcid.org/0000-0002-5687-7800"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hua Wu","raw_affiliation_strings":["Research Center for Human-Computer Intelligence, Shenyang Aerospace University, Shenyang, Liaoning, China"],"affiliations":[{"raw_affiliation_string":"Research Center for Human-Computer Intelligence, Shenyang Aerospace University, Shenyang, Liaoning, China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000645671","display_name":"Weiyi Kong","orcid":null},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiyi Kong","raw_affiliation_strings":["Research Center for Human-Computer Intelligence, Shenyang Aerospace University, Shenyang, Liaoning, China"],"affiliations":[{"raw_affiliation_string":"Research Center for Human-Computer Intelligence, Shenyang Aerospace University, Shenyang, Liaoning, China","institution_ids":["https://openalex.org/I125904092"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100677198"],"corresponding_institution_ids":["https://openalex.org/I125904092"],"apc_list":null,"apc_paid":null,"fwci":0.3497,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63619895,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"23","issue":"4","first_page":"2101","last_page":"2112"},"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":0.9945999979972839,"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":0.9937000274658203,"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":0.7779031991958618},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.6980127096176147},{"id":"https://openalex.org/keywords/argument","display_name":"Argument (complex analysis)","score":0.6693727970123291},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.6067601442337036},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5914243459701538},{"id":"https://openalex.org/keywords/gating","display_name":"Gating","score":0.5419697165489197},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5280949473381042},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5201461911201477},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.519964337348938},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.5036110281944275},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.4842971861362457},{"id":"https://openalex.org/keywords/fragment","display_name":"Fragment (logic)","score":0.48206788301467896},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4629424810409546},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40567153692245483},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.36134541034698486},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.329404354095459},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1444840133190155},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09473565220832825},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.08682271838188171},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.08565440773963928},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07182049751281738},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.06790047883987427}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7779031991958618},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6980127096176147},{"id":"https://openalex.org/C98184364","wikidata":"https://www.wikidata.org/wiki/Q1780131","display_name":"Argument (complex analysis)","level":2,"score":0.6693727970123291},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.6067601442337036},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5914243459701538},{"id":"https://openalex.org/C194544171","wikidata":"https://www.wikidata.org/wiki/Q21105679","display_name":"Gating","level":2,"score":0.5419697165489197},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5280949473381042},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5201461911201477},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.519964337348938},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.5036110281944275},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.4842971861362457},{"id":"https://openalex.org/C2776235265","wikidata":"https://www.wikidata.org/wiki/Q18392052","display_name":"Fragment (logic)","level":2,"score":0.48206788301467896},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4629424810409546},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40567153692245483},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36134541034698486},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.329404354095459},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1444840133190155},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09473565220832825},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.08682271838188171},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.08565440773963928},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07182049751281738},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.06790047883987427},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"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/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jcm-226772","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jcm-226772","pdf_url":null,"source":{"id":"https://openalex.org/S2765058733","display_name":"Journal of Computational Methods in Sciences and Engineering","issn_l":"1472-7978","issn":["1472-7978","1875-8983"],"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 Computational Methods in Sciences and Engineering","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":15,"referenced_works":["https://openalex.org/W1978072394","https://openalex.org/W2164343063","https://openalex.org/W2250999640","https://openalex.org/W2296283641","https://openalex.org/W2475245295","https://openalex.org/W2803884531","https://openalex.org/W2891553865","https://openalex.org/W2952370363","https://openalex.org/W2970684294","https://openalex.org/W3024298906","https://openalex.org/W3104597568","https://openalex.org/W3129047827","https://openalex.org/W3174691968","https://openalex.org/W3174945605","https://openalex.org/W3177448563"],"related_works":["https://openalex.org/W1973480752","https://openalex.org/W2805502594","https://openalex.org/W4253208712","https://openalex.org/W2031449089","https://openalex.org/W1603677234","https://openalex.org/W3132641048","https://openalex.org/W2217679042","https://openalex.org/W2525971763","https://openalex.org/W2984753899","https://openalex.org/W2783178962"],"abstract_inverted_index":{"Event":[0],"extraction,":[1,10],"as":[2],"one":[3],"of":[4,8,98,101,110],"the":[5,17,21,46,66,82,91,95,99,105,108,111,116],"difficult":[6],"tasks":[7,70],"information":[9,15,19,64],"can":[11],"quickly":[12],"obtain":[13],"valuable":[14],"from":[16,49],"massive":[18],"on":[20,32,115],"Internet.":[22],"This":[23],"paper":[24],"proposes":[25],"a":[26],"joint":[27],"event":[28,50,67,103],"extraction":[29,69],"model":[30,112],"based":[31],"RoBERTa-wwm-ext":[33],"and":[34,52,75,87,93],"gating":[35],"mechanism":[36],"for":[37],"document-level":[38],"long":[39],"text":[40],"data,":[41],"which":[42],"not":[43],"only":[44],"uses":[45,58],"prior":[47],"knowledge":[48],"types":[51],"pre-trained":[53],"language":[54],"models,":[55],"but":[56],"also":[57],"gated":[59],"fusion":[60],"module":[61],"to":[62,71],"aggregate":[63],"in":[65,90,104],"argument":[68,88],"enhance":[72],"entity":[73,77],"representation":[74],"splices":[76],"type":[78],"embedding,":[79],"thereby":[80],"enhancing":[81],"correlation":[83],"among":[84],"events,":[85],"arguments":[86,100],"roles":[89],"text,":[92],"improving":[94],"recognition":[96],"accuracy":[97],"each":[102],"document.":[106],"Finally,":[107],"effectiveness":[109],"is":[113],"verified":[114],"public":[117],"dataset.":[118]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}