{"id":"https://openalex.org/W4313480643","doi":"https://doi.org/10.1007/s41019-022-00203-6","title":"Multi-Model Fusion-Based Hierarchical Extraction for Chinese Epidemic Event","display_name":"Multi-Model Fusion-Based Hierarchical Extraction for Chinese Epidemic Event","publication_year":2023,"publication_date":"2023-01-02","ids":{"openalex":"https://openalex.org/W4313480643","doi":"https://doi.org/10.1007/s41019-022-00203-6","pmid":"https://pubmed.ncbi.nlm.nih.gov/36620528"},"language":"en","primary_location":{"id":"doi:10.1007/s41019-022-00203-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41019-022-00203-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41019-022-00203-6.pdf","source":{"id":"https://openalex.org/S2486411021","display_name":"Data Science and Engineering","issn_l":"2364-1185","issn":["2364-1185","2364-1541"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Science and Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s41019-022-00203-6.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084081529","display_name":"Zenghua Liao","orcid":"https://orcid.org/0009-0002-3155-2353"},"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":"Zenghua Liao","raw_affiliation_strings":["Laboratory for Big Data and Decision, National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory for Big Data and Decision, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101014381","display_name":"Zongqiang Yang","orcid":"https://orcid.org/0000-0002-2773-1175"},"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":"Zongqiang Yang","raw_affiliation_strings":["Laboratory for Big Data and Decision, National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory for Big Data and Decision, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010709877","display_name":"Peixin Huang","orcid":"https://orcid.org/0009-0005-5696-4735"},"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":"Peixin Huang","raw_affiliation_strings":["Laboratory for Big Data and Decision, National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory for Big Data and Decision, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102940051","display_name":"Ning Pang","orcid":"https://orcid.org/0000-0002-9870-6751"},"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":"Ning Pang","raw_affiliation_strings":["Laboratory for Big Data and Decision, National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory for Big Data and Decision, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014937762","display_name":"Xiang Zhao","orcid":"https://orcid.org/0000-0001-6339-0219"},"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":true,"raw_author_name":"Xiang Zhao","raw_affiliation_strings":["Laboratory for Big Data and Decision, National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-6339-0219","affiliations":[{"raw_affiliation_string":"Laboratory for Big Data and Decision, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5014937762"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":{"value":1290,"currency":"USD","value_usd":1290},"apc_paid":{"value":1290,"currency":"USD","value_usd":1290},"fwci":0.8597,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.72169674,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"8","issue":"1","first_page":"73","last_page":"83"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.3077999949455261,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.3077999949455261,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.20509999990463257,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.051899999380111694,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8304068446159363},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.6014342308044434},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.5519480109214783},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4561343789100647},{"id":"https://openalex.org/keywords/hierarchical-database-model","display_name":"Hierarchical database model","score":0.4162397086620331},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41319918632507324},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3904908299446106}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8304068446159363},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6014342308044434},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.5519480109214783},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4561343789100647},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.4162397086620331},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41319918632507324},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3904908299446106},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1007/s41019-022-00203-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41019-022-00203-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41019-022-00203-6.pdf","source":{"id":"https://openalex.org/S2486411021","display_name":"Data Science and Engineering","issn_l":"2364-1185","issn":["2364-1185","2364-1541"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Science and Engineering","raw_type":"journal-article"},{"id":"pmid:36620528","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36620528","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data science and engineering","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:9807097","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9807097","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC9807097/pdf/41019_2022_Article_203.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data Sci Eng","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:62a33779a8a34039b4f1db5afa274e83","is_oa":true,"landing_page_url":"https://doaj.org/article/62a33779a8a34039b4f1db5afa274e83","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data Science and Engineering, Vol 8, Iss 1, Pp 73-83 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s41019-022-00203-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41019-022-00203-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41019-022-00203-6.pdf","source":{"id":"https://openalex.org/S2486411021","display_name":"Data Science and Engineering","issn_l":"2364-1185","issn":["2364-1185","2364-1541"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Science and Engineering","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8700000047683716,"display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G5388974864","display_name":"\u7a00\u758f\u6837\u672c\u6761\u4ef6\u4e0b\u7684\u9886\u57df\u77e5\u8bc6\u56fe\u8c31\u83b7\u53d6\u4e0e\u5229\u7528\u7814\u7a76","funder_award_id":"61872446","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8218347068","display_name":null,"funder_award_id":"62272469","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4313480643.pdf"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W2039331562","https://openalex.org/W2059387088","https://openalex.org/W2115864922","https://openalex.org/W2211728022","https://openalex.org/W2250999640","https://openalex.org/W2265846598","https://openalex.org/W2475245295","https://openalex.org/W2509893387","https://openalex.org/W2573602082","https://openalex.org/W2782437235","https://openalex.org/W2788525741","https://openalex.org/W2891553865","https://openalex.org/W2952437275","https://openalex.org/W2962835228","https://openalex.org/W2963777632","https://openalex.org/W2964201905","https://openalex.org/W2964206023","https://openalex.org/W2965250913","https://openalex.org/W2970684294","https://openalex.org/W2971148526","https://openalex.org/W2997200074","https://openalex.org/W3005444529","https://openalex.org/W3023943971","https://openalex.org/W3036779180","https://openalex.org/W3092043163","https://openalex.org/W3100306564","https://openalex.org/W3117435054","https://openalex.org/W3128867615","https://openalex.org/W3136398196","https://openalex.org/W3152019416","https://openalex.org/W3154818064","https://openalex.org/W3163774486","https://openalex.org/W3177494822","https://openalex.org/W3198534705","https://openalex.org/W4210391403","https://openalex.org/W4225985257","https://openalex.org/W4283318382","https://openalex.org/W6702248584"],"related_works":["https://openalex.org/W2099421762","https://openalex.org/W2530546662","https://openalex.org/W2377297411","https://openalex.org/W2967030268","https://openalex.org/W2185253430","https://openalex.org/W4210345652","https://openalex.org/W3148217948","https://openalex.org/W3205103124","https://openalex.org/W2375788636","https://openalex.org/W1984333081"],"abstract_inverted_index":{"Abstract":[0],"In":[1,132],"recent":[2],"years,":[3],"Coronavirus":[4],"disease":[5],"2019":[6],"(COVID-19)":[7],"has":[8,185],"become":[9],"a":[10,102,115,136],"global":[11],"epidemic,":[12],"and":[13,21,71,95,166,188,200],"some":[14],"efforts":[15],"have":[16],"been":[17],"devoted":[18],"to":[19,140,205],"tracking":[20],"controlling":[22,42],"its":[23],"spread.":[24],"Extracting":[25],"structured":[26],"knowledge":[27],"from":[28],"involved":[29],"epidemic":[30,58,78,105,164],"case":[31,79],"reports":[32],"can":[33,161],"inform":[34],"the":[35,43,54,66,75,83,91,142,196,206],"surveillance":[36],"system,":[37],"which":[38,62],"is":[39,63],"important":[40],"for":[41],"spread":[44],"of":[45,56,68,77,85,144,147,208],"outbreaks.":[46],"Therefore,":[47],"in":[48,74],"this":[49,86,171],"paper,":[50],"we":[51,88,99,134],"focus":[52],"on":[53,154,170,177],"task":[55],"Chinese":[57,103],"event":[59,93],"extraction":[60],"(EE),":[61],"defined":[64],"as":[65],"detection":[67],"epidemic-related":[69,92],"events":[70,165],"corresponding":[72],"arguments":[73],"texts":[76],"reports.":[80],"To":[81],"facilitate":[82],"research":[84],"task,":[87],"first":[89],"define":[90],"types":[94],"argument":[96],"roles.":[97],"Then":[98],"manually":[100],"annotate":[101],"COVID-19":[104,108],"dataset,":[106],"named":[107,120],"Case":[109],"Report":[110],"(CCR).":[111],"We":[112],"also":[113,193],"propose":[114],"novel":[116],"hierarchical":[117,198],"EE":[118,149],"architecture,":[119],"m":[121],"ulti-model":[122],"f":[123],"usion-based":[124],"h":[125],"ierarchical":[126],"e":[127,129],"vent":[128],"xtraction":[130],"(MFHEE).":[131],"MFHEE,":[133],"introduce":[135],"multi-model":[137,201],"fusion":[138,202],"strategy":[139,203],"tackle":[141],"issue":[143],"recognition":[145],"bias":[146],"previous":[148],"models.":[150],"The":[151,173,190],"experimental":[152],"results":[153,176],"CCR":[155],"dataset":[156],"show":[157,181,194],"that":[158,182,195],"our":[159,183,209],"method":[160,184],"effectively":[162],"extract":[163],"outperforms":[167],"other":[168,178],"baselines":[169],"dataset.":[172],"comparative":[174],"experiments":[175],"generic":[179],"datasets":[180],"good":[186],"scalability":[187],"portability.":[189],"ablation":[191],"studies":[192],"proposed":[197],"structure":[199],"contribute":[204],"precision":[207],"model.":[210]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}