{"id":"https://openalex.org/W2973038827","doi":"https://doi.org/10.18653/v1/w19-3207","title":"KFU NLP Team at SMM4H 2019 Tasks: Want to Extract Adverse Drugs Reactions from Tweets? BERT to The Rescue","display_name":"KFU NLP Team at SMM4H 2019 Tasks: Want to Extract Adverse Drugs Reactions from Tweets? BERT to The Rescue","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2973038827","doi":"https://doi.org/10.18653/v1/w19-3207","mag":"2973038827"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w19-3207","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-3207","pdf_url":"https://www.aclweb.org/anthology/W19-3207.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop &amp; Shared Task","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W19-3207.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078878309","display_name":"Zulfat Miftahutdinov","orcid":null},"institutions":[{"id":"https://openalex.org/I21203515","display_name":"Kazan Federal University","ror":"https://ror.org/05256ym39","country_code":"RU","type":"education","lineage":["https://openalex.org/I21203515"]},{"id":"https://openalex.org/I2800906181","display_name":"St. Petersburg Department of Steklov Institute of Mathematics","ror":"https://ror.org/030h9s280","country_code":"RU","type":"facility","lineage":["https://openalex.org/I1313323035","https://openalex.org/I2800906181","https://openalex.org/I4210124601"]},{"id":"https://openalex.org/I4210141363","display_name":"Samsung (Russia)","ror":"https://ror.org/051an6p98","country_code":"RU","type":"company","lineage":["https://openalex.org/I4210141363"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Zulfat Miftahutdinov","raw_affiliation_strings":["Kazan Federal University, Kazan, Russia","Samsung-PDMI Joint AI Center, PDMI RAS, St. Petersburg, Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kazan Federal University, Kazan, Russia","institution_ids":["https://openalex.org/I21203515"]},{"raw_affiliation_string":"Samsung-PDMI Joint AI Center, PDMI RAS, St. Petersburg, Russia","institution_ids":["https://openalex.org/I4210141363","https://openalex.org/I2800906181"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019116960","display_name":"Ilseyar Alimova","orcid":"https://orcid.org/0000-0003-4528-6631"},"institutions":[{"id":"https://openalex.org/I21203515","display_name":"Kazan Federal University","ror":"https://ror.org/05256ym39","country_code":"RU","type":"education","lineage":["https://openalex.org/I21203515"]},{"id":"https://openalex.org/I2800906181","display_name":"St. Petersburg Department of Steklov Institute of Mathematics","ror":"https://ror.org/030h9s280","country_code":"RU","type":"facility","lineage":["https://openalex.org/I1313323035","https://openalex.org/I2800906181","https://openalex.org/I4210124601"]},{"id":"https://openalex.org/I4210141363","display_name":"Samsung (Russia)","ror":"https://ror.org/051an6p98","country_code":"RU","type":"company","lineage":["https://openalex.org/I4210141363"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Ilseyar Alimova","raw_affiliation_strings":["Kazan Federal University, Kazan, Russia","Samsung-PDMI Joint AI Center, PDMI RAS, St. Petersburg, Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kazan Federal University, Kazan, Russia","institution_ids":["https://openalex.org/I21203515"]},{"raw_affiliation_string":"Samsung-PDMI Joint AI Center, PDMI RAS, St. Petersburg, Russia","institution_ids":["https://openalex.org/I4210141363","https://openalex.org/I2800906181"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012311258","display_name":"Elena Tutubalina","orcid":"https://orcid.org/0000-0001-7936-0284"},"institutions":[{"id":"https://openalex.org/I21203515","display_name":"Kazan Federal University","ror":"https://ror.org/05256ym39","country_code":"RU","type":"education","lineage":["https://openalex.org/I21203515"]},{"id":"https://openalex.org/I2800906181","display_name":"St. Petersburg Department of Steklov Institute of Mathematics","ror":"https://ror.org/030h9s280","country_code":"RU","type":"facility","lineage":["https://openalex.org/I1313323035","https://openalex.org/I2800906181","https://openalex.org/I4210124601"]},{"id":"https://openalex.org/I4210141363","display_name":"Samsung (Russia)","ror":"https://ror.org/051an6p98","country_code":"RU","type":"company","lineage":["https://openalex.org/I4210141363"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Elena Tutubalina","raw_affiliation_strings":["Samsung-PDMI Joint AI Center, PDMI RAS, St. Petersburg, Russia","Kazan Federal University, Kazan, Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung-PDMI Joint AI Center, PDMI RAS, St. Petersburg, Russia","institution_ids":["https://openalex.org/I4210141363","https://openalex.org/I2800906181"]},{"raw_affiliation_string":"Kazan Federal University, Kazan, Russia","institution_ids":["https://openalex.org/I21203515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.326,"has_fulltext":true,"cited_by_count":31,"citation_normalized_percentile":{"value":0.93943872,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"52","last_page":"57"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9898999929428101,"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":0.9898999929428101,"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":0.9800000190734863,"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"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9610000252723694,"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":0.7904525995254517},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.7135820984840393},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.6611127257347107},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6377211213111877},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6058056354522705},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5788490176200867},{"id":"https://openalex.org/keywords/f1-score","display_name":"F1 score","score":0.5693240165710449},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5585245490074158},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5519834160804749},{"id":"https://openalex.org/keywords/named-entity-recognition","display_name":"Named-entity recognition","score":0.4941430389881134},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4439735412597656},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44189971685409546},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.44146254658699036},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4164489805698395},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.41401612758636475},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.32723021507263184},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.22460788488388062}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7904525995254517},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.7135820984840393},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6611127257347107},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6377211213111877},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6058056354522705},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5788490176200867},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.5693240165710449},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5585245490074158},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5519834160804749},{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.4941430389881134},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4439735412597656},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44189971685409546},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.44146254658699036},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4164489805698395},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.41401612758636475},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32723021507263184},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.22460788488388062},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/w19-3207","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-3207","pdf_url":"https://www.aclweb.org/anthology/W19-3207.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop &amp; Shared Task","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/w19-3207","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-3207","pdf_url":"https://www.aclweb.org/anthology/W19-3207.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop &amp; Shared Task","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6899999976158142,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G2322571202","display_name":null,"funder_award_id":"18-11-00284","funder_id":"https://openalex.org/F4320324099","funder_display_name":"Russian Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320324099","display_name":"Russian Science Foundation","ror":"https://ror.org/03y2gwe85"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2973038827.pdf","grobid_xml":"https://content.openalex.org/works/W2973038827.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W2102742655","https://openalex.org/W2131546905","https://openalex.org/W2157331557","https://openalex.org/W2296283641","https://openalex.org/W2509884321","https://openalex.org/W2605035112","https://openalex.org/W2752861104","https://openalex.org/W2779179495","https://openalex.org/W2808598571","https://openalex.org/W2893928366","https://openalex.org/W2895296143","https://openalex.org/W2896457183","https://openalex.org/W2897882775","https://openalex.org/W2907279416","https://openalex.org/W2911489562","https://openalex.org/W2914453913","https://openalex.org/W2950021574","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2972736338","https://openalex.org/W3098115739","https://openalex.org/W4285719527","https://openalex.org/W4301054811","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W4387517132","https://openalex.org/W3094868181","https://openalex.org/W3116252395","https://openalex.org/W4281560212","https://openalex.org/W3180764077","https://openalex.org/W2769084352","https://openalex.org/W4386322467","https://openalex.org/W2997394673","https://openalex.org/W4385574021","https://openalex.org/W4254089628"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"a":[3,34,72,80,97,133,146,166,190],"system":[4,117],"developed":[5],"for":[6,11,118,149,177],"the":[7,26,51,77,159,183],"Social":[8],"Media":[9],"Mining":[10],"Health":[12],"(SMM4H)":[13],"2019":[14,161,185],"shared":[15],"tasks.":[16,22],"Specifically,":[17],"we":[18],"participated":[19],"in":[20,71],"three":[21],"The":[23,48,115,140,171],"goals":[24],"of":[25,38,50,79,90,99,124,142,169,193],"first":[27,154,181],"two":[28],"tasks":[29],"are":[30],"to":[31,55,69,86,107,129],"classify":[32],"whether":[33],"tweet":[35],"contains":[36],"mentions":[37,63],"adverse":[39],"drug":[40],"reactions":[41],"(ADR)":[42],"and":[43,64,164,188],"extract":[44],"these":[45,67],"mentions,":[46],"respectively.":[47],"objective":[49],"third":[52],"task":[53],"is":[54,105],"build":[56],"an":[57,122],"end-toend":[58],"solution:":[59],"first,":[60],"detect":[61],"ADR":[62,178],"then":[65],"map":[66],"entities":[68],"concepts":[70],"controlled":[73],"vocabulary.":[74],"We":[75],"investigate":[76],"use":[78],"language":[81],"representation":[82],"model":[83,173],"BERT":[84,104,176],"trained":[85],"obtain":[87],"semantic":[88],"representations":[89],"social":[91],"media":[92],"texts.":[93],"Our":[94],"experiments":[95],"on":[96,111,175],"dataset":[98],"user":[100],"reviews":[101],"showed":[102],"that":[103],"superior":[106],"state-of-the-art":[108],"models":[109],"based":[110,174],"recurrent":[112],"neural":[113,143],"networks.":[114],"BERT-based":[116],"Task":[119,162,186],"1":[120],"obtained":[121,165,189],"F1":[123,131,168,192],"57.38%,":[125],"with":[126,145],"improvements":[127],"up":[128],"+7.19%":[130],"over":[132],"score":[134],"averaged":[135],"across":[136],"all":[137],"43":[138],"submissions.":[139],"ensemble":[141],"networks":[144],"voting":[147],"scheme":[148],"named":[150],"entity":[151],"recognition":[152],"ranked":[153,180],"among":[155],"9":[156],"teams":[157],"at":[158,182],"SMM4H":[160,184],"2":[163],"relaxed":[167,191],"65.8%.":[170],"end-to-end":[172],"normalization":[179],"3":[187],"43.2%.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
