{"id":"https://openalex.org/W4312830963","doi":"https://doi.org/10.1109/ijcnn55064.2022.9891886","title":"Event Coreference Resolution based on Convolutional Siamese network and Circle Loss","display_name":"Event Coreference Resolution based on Convolutional Siamese network and Circle Loss","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312830963","doi":"https://doi.org/10.1109/ijcnn55064.2022.9891886"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9891886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9891886","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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/A5082697134","display_name":"Beiya Dai","orcid":null},"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":"Beiya Dai","raw_affiliation_strings":["College of Computer, National University of Defense Technology,Changsha,China","College of Computer, National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology,Changsha,China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114172727","display_name":"Jiangang Qian","orcid":null},"institutions":[{"id":"https://openalex.org/I4210089056","display_name":"Beijing Microelectronics Technology Institute","ror":"https://ror.org/007y7ej30","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210089056"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangang Qian","raw_affiliation_strings":["School of Software and Microelectronics, Beijing University,Beijing,China","School of Software and Microelectronics, Beijing University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software and Microelectronics, Beijing University,Beijing,China","institution_ids":["https://openalex.org/I4210089056"]},{"raw_affiliation_string":"School of Software and Microelectronics, Beijing University, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062629554","display_name":"Shiqing Cheng","orcid":"https://orcid.org/0000-0001-5267-5569"},"institutions":[{"id":"https://openalex.org/I4210132047","display_name":"Beijing Radiation Center","ror":"https://ror.org/030t7nd77","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210132047"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiqing Cheng","raw_affiliation_strings":["Unit31511,Beijing,China","Unit31511, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Unit31511,Beijing,China","institution_ids":["https://openalex.org/I4210132047"]},{"raw_affiliation_string":"Unit31511, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043045076","display_name":"Linbo Qiao","orcid":"https://orcid.org/0000-0002-8285-2738"},"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":"Linbo Qiao","raw_affiliation_strings":["College of Computer, National University of Defense Technology,Changsha,China","College of Computer, National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology,Changsha,China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100440903","display_name":"Dongsheng Li","orcid":"https://orcid.org/0000-0001-9743-2034"},"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":"Dongsheng Li","raw_affiliation_strings":["College of Computer, National University of Defense Technology,Changsha,China","College of Computer, National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer, National University of Defense Technology,Changsha,China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"1","last_page":"7"},"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":0.9987999796867371,"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":0.9984999895095825,"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/coreference","display_name":"Coreference","score":0.9844245910644531},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8466372489929199},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.7207089066505432},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6547138690948486},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6533601880073547},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.651378870010376},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.5684038996696472},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5354998111724854},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.535098671913147},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.48073530197143555},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4159475266933441},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.41108250617980957},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3229568600654602},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.16522803902626038}],"concepts":[{"id":"https://openalex.org/C28076734","wikidata":"https://www.wikidata.org/wiki/Q63087","display_name":"Coreference","level":3,"score":0.9844245910644531},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8466372489929199},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.7207089066505432},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6547138690948486},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6533601880073547},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.651378870010376},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.5684038996696472},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5354998111724854},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.535098671913147},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.48073530197143555},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4159475266933441},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.41108250617980957},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3229568600654602},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.16522803902626038},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9891886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9891886","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W746041417","https://openalex.org/W1965693266","https://openalex.org/W2098345921","https://openalex.org/W2155069789","https://openalex.org/W2251552857","https://openalex.org/W2578696587","https://openalex.org/W2741515891","https://openalex.org/W2907265599","https://openalex.org/W2962691502","https://openalex.org/W2962751953","https://openalex.org/W2963033680","https://openalex.org/W2964222246","https://openalex.org/W3034303554","https://openalex.org/W3089283433","https://openalex.org/W3093830302","https://openalex.org/W3101095342","https://openalex.org/W3101528337","https://openalex.org/W3117131443","https://openalex.org/W3122890974","https://openalex.org/W3169597853","https://openalex.org/W3207806388","https://openalex.org/W4206334925","https://openalex.org/W6683166357","https://openalex.org/W6691816874","https://openalex.org/W6732288971","https://openalex.org/W6742030301","https://openalex.org/W6763893474","https://openalex.org/W6765909455","https://openalex.org/W6779068807","https://openalex.org/W6783535675","https://openalex.org/W6785225923"],"related_works":["https://openalex.org/W2259377089","https://openalex.org/W4281634851","https://openalex.org/W4386566736","https://openalex.org/W3041549465","https://openalex.org/W2380610138","https://openalex.org/W3171444480","https://openalex.org/W4206648670","https://openalex.org/W1495336436","https://openalex.org/W3212412177","https://openalex.org/W3173436410"],"abstract_inverted_index":{"The":[0],"purpose":[1],"of":[2,24,94,134,148],"the":[3,25,29,32,73,79,84,92,95,102,112,131,139,146,152],"cross-document":[4,15,153],"event":[5,63,67,106,115,136,149],"coreference":[6,16,34,105,114,154],"resolution":[7,17,116,155],"task":[8],"is":[9,108,117],"to":[10,77,100,127],"solve":[11,48],"multi-text":[12],"processing.":[13],"However,":[14],"has":[18],"not":[19,168],"been":[20,169],"fully":[21],"explored.":[22],"None":[23],"existing":[26],"methods":[27],"explore":[28],"situation":[30],"where":[31],"predicted":[33],"scores":[35],"are":[36],"also":[37],"low":[38,44,66],"when":[39],"similar":[40],"events":[41],"have":[42,167],"a":[43,50,57,123],"semantic":[45,68,132],"similarity.":[46,69],"To":[47],"such":[49],"problem,":[51],"in":[52,138],"this":[53],"paper,":[54],"we":[55,82],"propose":[56],"novel":[58],"model":[59,120,159],"by":[60,71,90],"focusing":[61],"on":[62,171],"classes":[64],"with":[65],"Specifically,":[70],"building":[72],"Siamese":[74],"network":[75],"framework":[76],"enhance":[78],"feature":[80],"representation,":[81],"convert":[83],"event-to-node":[85],"into":[86],"event-to-domain.":[87],"In":[88],"addition,":[89],"changing":[91],"form":[93],"problem":[96],"from":[97],"traditional":[98],"pairwise":[99],"listwise,":[101],"distance":[103,133],"between":[104],"nodes":[107],"greatly":[109,144],"reduced,":[110],"and":[111,143],"common":[113],"solved.":[118],"Our":[119],"only":[121],"employs":[122],"very":[124],"small":[125],"dataset":[126,156],"annotate":[128],"information,":[129],"increases":[130],"these":[135],"pairs":[137],"new":[140],"vector":[141],"space,":[142],"improves":[145],"effect":[147],"clustering.":[150],"For":[151],"ECB+,":[157],"our":[158],"achieves":[160],"better":[161],"results":[162],"than":[163],"other":[164],"models":[165],"that":[166],"fine-tuned":[170],"more":[172],"datasets":[173],"or":[174],"language":[175],"models.":[176]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}