{"id":"https://openalex.org/W3080730652","doi":"https://doi.org/10.1145/3409501.3409535","title":"Improving relation extraction by multi-task learning","display_name":"Improving relation extraction by multi-task learning","publication_year":2020,"publication_date":"2020-07-03","ids":{"openalex":"https://openalex.org/W3080730652","doi":"https://doi.org/10.1145/3409501.3409535","mag":"3080730652"},"language":"en","primary_location":{"id":"doi:10.1145/3409501.3409535","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3409501.3409535","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 4th High Performance Computing and Cluster Technologies Conference & 2020 3rd International Conference on Big Data 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/A5100398436","display_name":"Weijie Wang","orcid":"https://orcid.org/0000-0003-1532-1395"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weijie Wang","raw_affiliation_strings":["School of Data Science & Engineering, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Data Science & Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101578643","display_name":"Wenxin Hu","orcid":"https://orcid.org/0000-0001-8137-620X"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxin Hu","raw_affiliation_strings":["School of Data Science & Engineering, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Data Science & Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100398436"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":0.5302,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.72779847,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"152","last_page":"157"},"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":0.9995999932289124,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.9083722829818726},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.815908670425415},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.7972702980041504},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7322512865066528},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5637155175209045},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.5052054524421692},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.49711349606513977},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.4961584508419037},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45924168825149536},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.34632062911987305},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3137340545654297},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07407072186470032}],"concepts":[{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.9083722829818726},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.815908670425415},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.7972702980041504},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7322512865066528},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5637155175209045},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.5052054524421692},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.49711349606513977},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.4961584508419037},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45924168825149536},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.34632062911987305},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3137340545654297},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07407072186470032},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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":1,"locations":[{"id":"doi:10.1145/3409501.3409535","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3409501.3409535","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 4th High Performance Computing and Cluster Technologies Conference & 2020 3rd International Conference on Big Data 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":32,"referenced_works":["https://openalex.org/W1551842868","https://openalex.org/W2012179495","https://openalex.org/W2030408698","https://openalex.org/W2103931177","https://openalex.org/W2123143128","https://openalex.org/W2146191280","https://openalex.org/W2155454737","https://openalex.org/W2160487062","https://openalex.org/W2181042685","https://openalex.org/W2236688737","https://openalex.org/W2251135946","https://openalex.org/W2511964075","https://openalex.org/W2513378248","https://openalex.org/W2528512298","https://openalex.org/W2572908757","https://openalex.org/W2593831809","https://openalex.org/W2600659824","https://openalex.org/W2604610161","https://openalex.org/W2614752654","https://openalex.org/W2624871570","https://openalex.org/W2751936342","https://openalex.org/W2799054028","https://openalex.org/W2887428522","https://openalex.org/W2892094955","https://openalex.org/W2907630459","https://openalex.org/W2956879910","https://openalex.org/W2963171262","https://openalex.org/W2970115347","https://openalex.org/W2971031791","https://openalex.org/W2987386900","https://openalex.org/W6600995651","https://openalex.org/W6629296869"],"related_works":["https://openalex.org/W2976808399","https://openalex.org/W2609844752","https://openalex.org/W2981341912","https://openalex.org/W4385734297","https://openalex.org/W4285246823","https://openalex.org/W4226278302","https://openalex.org/W2547211086","https://openalex.org/W4221160509","https://openalex.org/W3114142812","https://openalex.org/W4380551175"],"abstract_inverted_index":{"Relation":[0],"extraction":[1,10,17,31,52,88],"is":[2],"a":[3,29],"subtask":[4],"of":[5],"information":[6],"extraction.":[7],"Current":[8],"relation":[9,16,30,51,87],"methods":[11,89],"are":[12,45],"mainly":[13],"designed":[14],"for":[15],"tasks,":[18],"and":[19,54],"they":[20],"use":[21],"limited":[22],"knowledge.":[23],"In":[24],"this":[25],"paper,":[26],"we":[27,55],"propose":[28],"method":[32,82],"based":[33,72],"on":[34,73,90],"multi-task":[35,62],"learning.":[36],"It":[37],"uses":[38],"multiple":[39],"tasks":[40],"to":[41,47,59],"learn":[42,48],"features":[43],"that":[44,80],"hard":[46],"from":[49],"the":[50,61,74,91],"task,":[53],"add":[56],"knowledge":[57],"distillation":[58],"help":[60],"model":[63,77],"perform":[64],"better":[65,84],"than":[66,85],"its":[67],"single-task":[68],"counterparts.":[69],"The":[70],"experiments":[71],"pre-trained":[75],"language":[76],"BERT":[78],"show":[79],"our":[81],"performs":[83],"most":[86],"SemEval2010-task8":[92],"dataset.":[93]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}