{"id":"https://openalex.org/W3134098426","doi":"https://doi.org/10.1145/3446132.3446397","title":"Context Event Features and Event Embedding Enhanced Event Detection","display_name":"Context Event Features and Event Embedding Enhanced Event Detection","publication_year":2020,"publication_date":"2020-12-24","ids":{"openalex":"https://openalex.org/W3134098426","doi":"https://doi.org/10.1145/3446132.3446397","mag":"3134098426"},"language":"en","primary_location":{"id":"doi:10.1145/3446132.3446397","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3446132.3446397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 3rd International Conference on Algorithms, Computing and Artificial Intelligence","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/A5053768421","display_name":"Xin Shi","orcid":"https://orcid.org/0000-0002-0243-1539"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Shi","raw_affiliation_strings":["University of Electronic Science & Technology of China, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science & Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006214126","display_name":"Xiaoyang Zeng","orcid":"https://orcid.org/0009-0001-9928-8782"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyang Zeng","raw_affiliation_strings":["University of Electronic Science & Technology of China, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science & Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090305024","display_name":"Jieyun Wu","orcid":"https://orcid.org/0000-0002-6135-4545"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Wu","raw_affiliation_strings":["University of Electronic Science & Technology of China, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science & Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102008799","display_name":"Mengshu Hou","orcid":"https://orcid.org/0000-0002-5283-7318"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengshu Hou","raw_affiliation_strings":["University of Electronic Science & Technology of China, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science & Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101693600","display_name":"Hao Zhu","orcid":"https://orcid.org/0000-0002-6756-9571"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zhu","raw_affiliation_strings":["University of Electronic Science & Technology of China, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science & Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5053768421"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.1326,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.58287159,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9976000189781189,"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/T11719","display_name":"Data Quality and Management","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7396861910820007},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.7253337502479553},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5717532634735107},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5443148612976074},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.49896931648254395},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.43682754039764404},{"id":"https://openalex.org/keywords/complex-event-processing","display_name":"Complex event processing","score":0.43513861298561096},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4264422059059143},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.41022735834121704},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.409228652715683},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.37533098459243774},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09963303804397583}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7396861910820007},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.7253337502479553},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5717532634735107},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5443148612976074},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.49896931648254395},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.43682754039764404},{"id":"https://openalex.org/C123606473","wikidata":"https://www.wikidata.org/wiki/Q907918","display_name":"Complex event processing","level":3,"score":0.43513861298561096},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4264422059059143},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.41022735834121704},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.409228652715683},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37533098459243774},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09963303804397583},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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":1,"locations":[{"id":"doi:10.1145/3446132.3446397","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3446132.3446397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 3rd International Conference on Algorithms, Computing and Artificial Intelligence","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":19,"referenced_works":["https://openalex.org/W2130714105","https://openalex.org/W2165516035","https://openalex.org/W2165962657","https://openalex.org/W2250575108","https://openalex.org/W2250999640","https://openalex.org/W2475245295","https://openalex.org/W2562564313","https://openalex.org/W2739918945","https://openalex.org/W2775730905","https://openalex.org/W2788322837","https://openalex.org/W2788474500","https://openalex.org/W2788525741","https://openalex.org/W2798563357","https://openalex.org/W2798636921","https://openalex.org/W2913660829","https://openalex.org/W2952437275","https://openalex.org/W2952451326","https://openalex.org/W2980708516","https://openalex.org/W6666761814"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W2375873920","https://openalex.org/W2183306018","https://openalex.org/W1607805252","https://openalex.org/W2397597979","https://openalex.org/W2799235612","https://openalex.org/W4308672222","https://openalex.org/W1835640443","https://openalex.org/W413387906","https://openalex.org/W2072592647"],"abstract_inverted_index":{"Extracting":[0],"valuable":[1],"information":[2,21,33,67],"from":[3],"text":[4],"has":[5],"always":[6],"been":[7],"a":[8,53,87,92,116],"hot":[9],"point":[10],"for":[11],"research":[12],"and":[13,34,68,142,150],"event":[14,27,42,59,69,74,79,84,97,106,148],"detection":[15,28,60,75],"is":[16,136],"an":[17],"essential":[18],"subtask":[19],"of":[20,26,147],"extraction.":[22],"Most":[23],"existing":[24,140],"methods":[25],"only":[29],"focus":[30],"on":[31,127],"sentence-level":[32],"do":[35],"not":[36],"consider":[37],"the":[38,73,96,103,123,128,145],"correlation":[39,70,98,149],"between":[40,105],"different":[41],"types.":[43],"To":[44,77],"address":[45],"these":[46],"problems,":[47],"in":[48],"this":[49],"paper,":[50],"we":[51,81,114],"propose":[52],"novel":[54],"pre-trained":[55],"language":[56],"model":[57,135],"based":[58],"framework":[61],"named":[62],"CFEE":[63],"that":[64,132],"utilizes":[65],"document-level":[66,112,151],"to":[71,110,121],"enhance":[72],"task.":[76],"obtain":[78],"correlation,":[80],"project":[82],"all":[83],"types":[85],"into":[86],"shared":[88],"semantic":[89],"space":[90],"through":[91],"Skip-gram":[93],"model,":[94],"where":[95],"can":[99],"be":[100],"represented":[101],"as":[102],"distance":[104],"embeddings.":[107],"In":[108],"order":[109],"capture":[111],"information,":[113],"utilize":[115],"bidirectional":[117],"recurrent":[118],"neural":[119],"network":[120],"fuse":[122],"context":[124],"information.":[125,152],"Experiments":[126],"ACE2005":[129],"dataset":[130],"demonstrate":[131,144],"our":[133],"proposed":[134],"better":[137],"than":[138],"most":[139],"methods,":[141],"also":[143],"effectiveness":[146]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}