Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/62769
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Campo DC | Valor | Idioma |
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dc.contributor.author | Goncalves, Sergio | por |
dc.contributor.author | Cortez, Paulo | por |
dc.contributor.author | Moro, Sergio | por |
dc.date.accessioned | 2019-12-21T12:21:30Z | - |
dc.date.available | 2019-12-21T12:21:30Z | - |
dc.date.issued | 2018 | - |
dc.identifier.isbn | 9783030014230 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | https://hdl.handle.net/1822/62769 | - |
dc.description.abstract | The classification of abstract sentences is a valuable tool to support scientific database querying, to summarize relevant literature works and to assist in the writing of new abstracts. This study proposes a novel deep learning approach based on a convolutional layer and a bi-directional gated recurrent unit to classify sentences of abstracts. The proposed neural network was tested on a sample of 20 thousand abstracts from the biomedical domain. Competitive results were achieved, with weight-averaged precision, recall and F1-score values around 91%, which are higher when compared to a state-of-the-art neural network. | por |
dc.description.sponsorship | This work was supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT Fundacao para a Ciencia e Tecnologia within the Project Scope: UID/CEC/00319/2013. | por |
dc.language.iso | eng | por |
dc.publisher | Springer | por |
dc.relation | info:eu-repo/grantAgreement/FCT/5876/147280/PT | por |
dc.rights | openAccess | por |
dc.subject | Bi-directional gated recurrent unit | por |
dc.subject | Sentence classification | por |
dc.subject | Scientific articles | por |
dc.subject | Text mining | por |
dc.subject | Deep learning | por |
dc.title | A deep learning approach for sentence classification of scientific abstracts | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
oaire.citationStartPage | 479 | por |
oaire.citationEndPage | 488 | por |
oaire.citationVolume | 11141 | por |
dc.date.updated | 2019-12-20T14:50:06Z | - |
dc.identifier.doi | 10.1007/978-3-030-01424-7_47 | por |
dc.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | por |
dc.subject.wos | Science & Technology | - |
sdum.export.identifier | 5437 | - |
sdum.journal | Lecture Notes in Computer Science | por |
sdum.conferencePublication | ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2018, PT III | por |
sdum.bookTitle | ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2018, PT III | por |
oaire.version | AM | por |
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Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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icann181.pdf | Author's Accepted Manuscript | 323,33 kB | Adobe PDF | Ver/Abrir |