{"id":"https://openalex.org/W4210770523","doi":"https://doi.org/10.1080/09540091.2022.2026295","title":"Entity and relation collaborative extraction approach based on multi-head attention and gated mechanism","display_name":"Entity and relation collaborative extraction approach based on multi-head attention and gated mechanism","publication_year":2022,"publication_date":"2022-02-04","ids":{"openalex":"https://openalex.org/W4210770523","doi":"https://doi.org/10.1080/09540091.2022.2026295"},"language":"en","primary_location":{"id":"doi:10.1080/09540091.2022.2026295","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2022.2026295","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2022.2026295?needAccess=true","source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2022.2026295?needAccess=true","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101671769","display_name":"Wei Zhao","orcid":"https://orcid.org/0000-0002-5422-5657"},"institutions":[{"id":"https://openalex.org/I118612203","display_name":"Hunan Police Academy","ror":"https://ror.org/02gh10772","country_code":"CN","type":"education","lineage":["https://openalex.org/I118612203"]},{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Zhao","raw_affiliation_strings":["College of Computer, National University of Defense Technology, Changsha, People's Republic of China","Hunan Provincial Key Laboratory of Network Investigational Technology, Hunan Police Academy, Changsha, Hunan, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology, Changsha, People's Republic of China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"Hunan Provincial Key Laboratory of Network Investigational Technology, Hunan Police Academy, Changsha, Hunan, People's Republic of China","institution_ids":["https://openalex.org/I118612203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089008240","display_name":"Shan Zhao","orcid":"https://orcid.org/0000-0003-4503-8259"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Zhao","raw_affiliation_strings":["College of Computer, National University of Defense Technology, Changsha, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology, Changsha, People's Republic of China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053674695","display_name":"Shuhui Chen","orcid":"https://orcid.org/0000-0001-7413-8174"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuhui Chen","raw_affiliation_strings":["College of Computer, National University of Defense Technology, Changsha, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology, Changsha, People's Republic of China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067675188","display_name":"Tien\u2010Hsiung Weng","orcid":"https://orcid.org/0000-0003-3244-4127"},"institutions":[{"id":"https://openalex.org/I177918364","display_name":"Providence University","ror":"https://ror.org/03fcpsq87","country_code":"TW","type":"education","lineage":["https://openalex.org/I177918364"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tien-Hsiung Weng","raw_affiliation_strings":["Department of Computer Science and Information Engineering Providence University Taiwan, Computer Science and Information Engineering Providence University Taiwan, Taichung City Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering Providence University Taiwan, Computer Science and Information Engineering Providence University Taiwan, Taichung City Taiwan","institution_ids":["https://openalex.org/I177918364"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047402946","display_name":"Wenjie Kang","orcid":"https://orcid.org/0000-0003-4476-9578"},"institutions":[{"id":"https://openalex.org/I118612203","display_name":"Hunan Police Academy","ror":"https://ror.org/02gh10772","country_code":"CN","type":"education","lineage":["https://openalex.org/I118612203"]},{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"WenJie Kang","raw_affiliation_strings":["Hunan Provincial Key Laboratory of Network Investigational Technology, Hunan Police Academy, Changsha, Hunan, People's Republic of China","Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hunan Provincial Key Laboratory of Network Investigational Technology, Hunan Police Academy, Changsha, Hunan, People's Republic of China","institution_ids":["https://openalex.org/I118612203"]},{"raw_affiliation_string":"Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha, People's Republic of China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101671769"],"corresponding_institution_ids":["https://openalex.org/I118612203","https://openalex.org/I170215575"],"apc_list":{"value":1270,"currency":"USD","value_usd":1270},"apc_paid":{"value":1270,"currency":"USD","value_usd":1270},"fwci":0.8323,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.76767299,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"34","issue":"1","first_page":"670","last_page":"686"},"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":0.9972000122070312,"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":0.9962999820709229,"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":0.8808513283729553},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.8637322783470154},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.6620543003082275},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.6517179608345032},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.6246249675750732},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5593159198760986},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5513675808906555},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4989309310913086},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.49122923612594604},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4564895033836365},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.43815144896507263},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4061673581600189},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3654367923736572},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35921046137809753},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.0738883912563324}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8808513283729553},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.8637322783470154},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.6620543003082275},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.6517179608345032},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.6246249675750732},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5593159198760986},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5513675808906555},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4989309310913086},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49122923612594604},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4564895033836365},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.43815144896507263},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4061673581600189},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3654367923736572},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35921046137809753},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0738883912563324},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/09540091.2022.2026295","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2022.2026295","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2022.2026295?needAccess=true","source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8d2f941d4fa34648a0f6c0ae2036d491","is_oa":false,"landing_page_url":"https://doaj.org/article/8d2f941d4fa34648a0f6c0ae2036d491","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":"Connection Science, Vol 34, Iss 1, Pp 670-686 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/09540091.2022.2026295","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2022.2026295","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2022.2026295?needAccess=true","source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4210770523.pdf"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W1996787131","https://openalex.org/W1997912386","https://openalex.org/W2020278455","https://openalex.org/W2095074673","https://openalex.org/W2129767020","https://openalex.org/W2132093718","https://openalex.org/W2132516856","https://openalex.org/W2250999640","https://openalex.org/W2251091211","https://openalex.org/W2252135867","https://openalex.org/W2405223529","https://openalex.org/W2564980658","https://openalex.org/W2567289819","https://openalex.org/W2618011341","https://openalex.org/W2741956709","https://openalex.org/W2769387903","https://openalex.org/W2799125718","https://openalex.org/W2808667805","https://openalex.org/W2907265599","https://openalex.org/W2949922292","https://openalex.org/W2953738034","https://openalex.org/W2957783787","https://openalex.org/W2962739339","https://openalex.org/W2963171262","https://openalex.org/W2963569987","https://openalex.org/W2963602416","https://openalex.org/W2963997908","https://openalex.org/W2966683369","https://openalex.org/W2984582583","https://openalex.org/W2997362387","https://openalex.org/W2997876626","https://openalex.org/W3014595877","https://openalex.org/W3021896175","https://openalex.org/W3025413549","https://openalex.org/W3035229828","https://openalex.org/W3035259209","https://openalex.org/W3041454767","https://openalex.org/W3078357177","https://openalex.org/W3096150952","https://openalex.org/W3101095342","https://openalex.org/W3105063288","https://openalex.org/W3105831202","https://openalex.org/W3126177318","https://openalex.org/W3126929272","https://openalex.org/W3156977337","https://openalex.org/W3164738730","https://openalex.org/W3173892794","https://openalex.org/W3182245181","https://openalex.org/W3191622740","https://openalex.org/W3193855266","https://openalex.org/W4285718364","https://openalex.org/W6677665046","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W2888033806","https://openalex.org/W4319940250","https://openalex.org/W4379744446","https://openalex.org/W2753023842","https://openalex.org/W2807524541","https://openalex.org/W4224089748","https://openalex.org/W4299912061","https://openalex.org/W2976808399","https://openalex.org/W2605526599","https://openalex.org/W3216747561"],"abstract_inverted_index":{"Entity":[0],"and":[1,12,78,90,133,164,173],"relation":[2,79,120,165,181],"extraction":[3,80,166,182],"has":[4,35,152],"been":[5,17,36],"widely":[6],"studied":[7],"in":[8,19,39,76,159,189],"natural":[9],"language":[10],"processing,":[11],"some":[13],"joint":[14],"methods":[15],"have":[16,54],"proposed":[18,96],"recent":[20],"years.":[21],"However,":[22,49],"existing":[23,187],"studies":[24],"still":[25,74],"suffer":[26],"from":[27],"two":[28,123],"problems.":[29,100],"Firstly,":[30,101],"the":[31,43,57,67,104,116,119,131,140,168,177,190],"token":[32,132],"space":[33,45,59,106],"information":[34,46,60,107],"fully":[37],"utilized":[38],"those":[40],"studies,":[41],"while":[42],"label":[44,58,105],"is":[47,73,95],"underutilized.":[48],"a":[50,85,110],"few":[51],"preliminary":[52],"works":[53],"proven":[55],"that":[56,150],"could":[61,114,144],"contribute":[62],"to":[63,97,129],"this":[64,83,138],"task.":[65],"Secondly,":[66],"performance":[68,117],"of":[69,118,161,180],"relevant":[70,141],"entities":[71,142],"detection":[72,143],"unsatisfactory":[75],"entity":[77,162],"tasks.":[81],"In":[82,137],"paper,":[84],"new":[86],"model":[87],"GANCE":[88,102,151],"(Gated":[89],"Attentive":[91],"Network":[92],"Collaborative":[93],"Extracting)":[94],"address":[98],"these":[99],"exploits":[103],"by":[108,184],"applying":[109],"gating":[111],"mechanism,":[112],"which":[113],"improve":[115],"extraction.":[121],"Then,":[122],"multi-head":[124],"attention":[125],"modules":[126],"are":[127],"designed":[128],"update":[130],"token-label":[134],"fusion":[135],"representation.":[136],"way,":[139],"be":[145],"solved.":[146],"Experimental":[147],"results":[148],"demonstrate":[149],"better":[153],"accuracy":[154],"than":[155],"several":[156],"competitive":[157],"approaches":[158,188],"terms":[160],"recognition":[163],"on":[167],"CoNLL04":[169],"dataset":[170],"at":[171],"90.32%":[172],"73.59%,":[174],"respectively.":[175],"Moreover,":[176],"F1":[178],"score":[179],"increased":[183],"1.24%":[185],"over":[186],"ADE":[191],"dataset.":[192]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":3}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2025-10-10T00:00:00"}
