{"id":"https://openalex.org/W4399423168","doi":"https://doi.org/10.1145/3652583.3658076","title":"A Graph Convolution Network with a POS-aware Filter and Context Enhancement Mechanism for Event Detection","display_name":"A Graph Convolution Network with a POS-aware Filter and Context Enhancement Mechanism for Event Detection","publication_year":2024,"publication_date":"2024-05-30","ids":{"openalex":"https://openalex.org/W4399423168","doi":"https://doi.org/10.1145/3652583.3658076"},"language":"en","primary_location":{"id":"doi:10.1145/3652583.3658076","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3652583.3658076","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3652583.3658076","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3652583.3658076","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019259577","display_name":"Xintao Jiao","orcid":"https://orcid.org/0009-0004-3095-6051"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xintao Jiao","raw_affiliation_strings":["South China Normal University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0004-3095-6051","affiliations":[{"raw_affiliation_string":"South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004407585","display_name":"J. F. Chen","orcid":"https://orcid.org/0009-0007-1228-5866"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiansheng Chen","raw_affiliation_strings":["South China Normal University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0007-1228-5866","affiliations":[{"raw_affiliation_string":"South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103068713","display_name":"Jiale Liu","orcid":"https://orcid.org/0009-0002-3997-4673"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiale Liu","raw_affiliation_strings":["South China Normal University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0002-3997-4673","affiliations":[{"raw_affiliation_string":"South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5019259577"],"corresponding_institution_ids":["https://openalex.org/I187400657"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06255465,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"285","last_page":"292"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9977999925613403,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9976999759674072,"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":0.8147018551826477},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6139166951179504},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5891793370246887},{"id":"https://openalex.org/keywords/dependency-graph","display_name":"Dependency graph","score":0.5482845306396484},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4680822491645813},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.45494863390922546},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.43952205777168274},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43223845958709717},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.42879998683929443},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3252672553062439},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3241982161998749},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.10102421045303345},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.07240250706672668}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8147018551826477},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6139166951179504},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5891793370246887},{"id":"https://openalex.org/C16311509","wikidata":"https://www.wikidata.org/wiki/Q4148050","display_name":"Dependency graph","level":3,"score":0.5482845306396484},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4680822491645813},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.45494863390922546},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.43952205777168274},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43223845958709717},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.42879998683929443},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3252672553062439},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3241982161998749},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.10102421045303345},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.07240250706672668},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3652583.3658076","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3652583.3658076","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3652583.3658076","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3652583.3658076","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3652583.3658076","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3652583.3658076","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399423168.pdf","grobid_xml":"https://content.openalex.org/works/W4399423168.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W2788474500","https://openalex.org/W2890373807","https://openalex.org/W2964051675","https://openalex.org/W2970763364","https://openalex.org/W3098881736","https://openalex.org/W3101701554","https://openalex.org/W3134098426","https://openalex.org/W3211807332","https://openalex.org/W4283801565","https://openalex.org/W4307091486","https://openalex.org/W4366308386","https://openalex.org/W6927916266"],"related_works":["https://openalex.org/W1978572805","https://openalex.org/W2383807498","https://openalex.org/W1997992934","https://openalex.org/W1987225439","https://openalex.org/W4238188170","https://openalex.org/W2125114371","https://openalex.org/W2019977573","https://openalex.org/W2149980199","https://openalex.org/W4226363941","https://openalex.org/W3200266554"],"abstract_inverted_index":{"Event":[0],"detection":[1],"(ED)":[2],"is":[3,108,123,157],"a":[4,77,83,92,116,135],"task":[5],"that":[6],"focuses":[7],"on":[8,148],"identifying":[9],"event":[10],"instances":[11],"in":[12,30,64,134],"texts.":[13],"Many":[14],"previous":[15],"studies":[16],"have":[17],"demonstrated":[18],"the":[19,38,48,57,101,127,152],"effectiveness":[20],"of":[21,60,131,154],"syntactic":[22],"dependency":[23],"trees":[24],"and":[25,43,86,105,121],"graph":[26,51,79,112],"convolution":[27,80,113],"networks":[28],"(GCN)":[29],"ED":[31],"tasks.":[32],"However,":[33],"such":[34],"methods":[35,133,147],"haven't":[36],"utilized":[37],"correlation":[39,102],"between":[40,103,119],"part-of-speech":[41],"(POS)":[42],"keyword":[44,106],"distribution":[45],"to":[46,56,69,125],"filter":[47,85],"noise":[49],"from":[50],"convolution.":[52],"In":[53,72],"addition,":[54],"owning":[55],"over-smoothing":[58],"problem":[59],"GCN,":[61],"their":[62],"abilities":[63],"contextual":[65],"understanding":[66,129],"also":[67],"need":[68],"be":[70],"improved.":[71],"this":[73,155],"paper,":[74],"we":[75],"propose":[76],"novel":[78],"network":[81],"with":[82],"POS-aware":[84],"context":[87,128],"enhancement":[88],"mechanism":[89],"(GCN-PFCE).":[90],"Specifically,":[91],"gating":[93],"unit":[94],"controlled":[95],"by":[96],"POS,":[97],"which":[98],"can":[99],"learn":[100],"POS":[104],"distribution,":[107],"added":[109],"after":[110],"each":[111],"layer.":[114],"Besides,":[115],"parallel":[117],"structure":[118],"BERT":[120],"GCN":[122],"implemented":[124],"enhance":[126],"ability":[130],"GCN-based":[132],"better":[136],"way.":[137],"The":[138],"proposed":[139],"model":[140],"achieves":[141],"significant":[142],"improvement":[143],"over":[144],"competitive":[145],"baseline":[146],"ACE2005":[149],"dataset.":[150],"Additionally,":[151],"code":[153],"paper":[156],"released":[158],"as":[159],"open-source":[160],"at":[161],"https://github.com/Jiansheng-Chen/GCN-PFCE.":[162]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
