Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10071/16641
Registo completo
Campo DC | Valor | Idioma |
---|---|---|
dc.contributor.author | Gonçalves, S. | - |
dc.contributor.author | Cortez, P. | - |
dc.contributor.author | Moro, S. | - |
dc.contributor.editor | V. Kurkova et al. | - |
dc.date.accessioned | 2018-10-11T10:14:58Z | - |
dc.date.available | 2018-10-11T10:14:58Z | - |
dc.date.issued | 2018 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | https://ciencia.iscte-iul.pt/id/ci-pub-49715 | - |
dc.identifier.uri | http://hdl.handle.net/10071/16641 | - |
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. | eng |
dc.language.iso | eng | - |
dc.publisher | Springer | - |
dc.relation | POCI-01-0145-FEDER-007043 | - |
dc.relation | UID/MULTI/0446/2013 | - |
dc.relation | UID/CEC/00319/2013 | - |
dc.rights | openAccess | - |
dc.subject | Bi-directional gated recurrent unit | eng |
dc.subject | Sentence classification | eng |
dc.subject | Text mining | eng |
dc.subject | Deep learning | eng |
dc.subject | Scientific articles | eng |
dc.title | A deep learning approach for sentence classification of scientific abstracts | eng |
dc.type | conferenceObject | - |
dc.event.type | Conferência | pt |
dc.event.location | Island of Rhodes, Greece | eng |
dc.event.date | 2018 | - |
dc.pagination | 479 - 488 | - |
dc.peerreviewed | yes | - |
dc.journal | Artificial Neural Networks and Machine Learning – ICANN 2018 | - |
degois.publication.firstPage | 479 | - |
degois.publication.lastPage | 488 | - |
degois.publication.location | Island of Rhodes, Greece | eng |
degois.publication.title | A deep learning approach for sentence classification of scientific abstracts | eng |
dc.description.version | info:eu-repo/semantics/acceptedVersion | - |
dc.identifier.doi | 10.1007/978-3-030-01424-7_47 | - |
dc.subject.fos | Domínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informação | por |
Aparece nas coleções: | ISTAR-CRI - Comunicações a conferências internacionais |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
---|---|---|---|---|
2018_ICANN-GoncalvesCortezMoro-PosPrint.pdf | Pós-print | 400,47 kB | Adobe PDF | Ver/Abrir |
Todos os registos no repositório estão protegidos por leis de copyright, com todos os direitos reservados.