Ensemble of Convolutional Neural Networks for Medicine Intake Recognition in Twitter

dc.contributor.authorKai Hakala
dc.contributor.authorFarrokh Mehryary
dc.contributor.authorHans Moen
dc.contributor.authorSuwisa Kaewphan
dc.contributor.authorTapio Salakoski
dc.contributor.authorFilip Ginter
dc.contributor.organizationfi=hoitotieteen laitos|en=Department of Nursing Science|
dc.contributor.organizationfi=kieli- ja puheteknologia|en=Language and Speech Technology|
dc.contributor.organizationfi=tietojenkäsittelytiede|en=Computer Science|
dc.contributor.organization-code1.2.246.10.2458963.20.47465613983
dc.contributor.organization-code2606803
dc.contributor.organization-code2606805
dc.converis.publication-id28245409
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/28245409
dc.date.accessioned2022-10-28T14:39:17Z
dc.date.available2022-10-28T14:39:17Z
dc.description.abstract<p>We present the results from our participation in the 2nd Social Media Mining for Health Applications Shared Task – Task 2. The goal of this task is to develop systems capable of recognizing mentions of medication intake in Twitter. Our best performing classification system is an ensemble of neural networks with features generated by word- and character-level convolutional neural network channels and a condensed weighted bag-of-words representation. A relatively strong performance is achieved, with an F-score of 66.3 according to the official evaluation, resulting in the 5th place in the shared task with performance close to the best systems created by other participating teams.<br></p>
dc.format.pagerange59
dc.format.pagerange63
dc.identifier.issn1613-0073
dc.identifier.jour-issn1613-0073
dc.identifier.olddbid189502
dc.identifier.oldhandle10024/172596
dc.identifier.urihttps://www.utupub.fi/handle/11111/44570
dc.identifier.urlhttp://ceur-ws.org/Vol-1996/paper11.pdf
dc.identifier.urnURN:NBN:fi-fe2021042717806
dc.language.isoen
dc.okm.affiliatedauthorHakala, Kai
dc.okm.affiliatedauthorMehryary, Farrokh
dc.okm.affiliatedauthorMoen, Hans
dc.okm.affiliatedauthorKaewphan, Suwisa
dc.okm.affiliatedauthorSalakoski, Tapio
dc.okm.affiliatedauthorGinter, Filip
dc.okm.affiliatedauthorDataimport, Hoitotieteen laitos
dc.okm.discipline113 Computer and information sciencesen_GB
dc.okm.discipline3141 Health care scienceen_GB
dc.okm.discipline113 Tietojenkäsittely ja informaatiotieteetfi_FI
dc.okm.discipline3141 Terveystiedefi_FI
dc.okm.internationalcopublicationnot an international co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA4 Conference Article
dc.relation.conferenceSocial Media Mining for Health Research and Applications
dc.relation.ispartofjournalCEUR Workshop Proceedings
dc.relation.ispartofseriesCEUR Workshop Proceedings
dc.relation.volume1996
dc.source.identifierhttps://www.utupub.fi/handle/10024/172596
dc.titleEnsemble of Convolutional Neural Networks for Medicine Intake Recognition in Twitter
dc.title.bookProceedings of the 2nd Social Media Mining for Health Research and Applications Workshop (SMM4H 2017)
dc.year.issued2017

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