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Title: A deep learning approach for sentence classification of scientific abstracts
Authors: Gonçalves, S.
Cortez, P.
Moro, S.
Editors: V. Kurkova et al.
Keywords: Bi-directional gated recurrent unit
Sentence classification
Text mining
Deep learning
Scientific articles
Issue Date: 2018
Publisher: Springer
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.
Peer reviewed: yes
DOI: 10.1007/978-3-030-01424-7_47
ISSN: 0302-9743
Appears in Collections:ISTAR-CRI - Comunicações a conferências internacionais

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