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2018 | OriginalPaper | Buchkapitel

A Deep Learning Approach for Sentence Classification of Scientific Abstracts

verfasst von : Sérgio Gonçalves, Paulo Cortez, Sérgio Moro

Erschienen in: Artificial Neural Networks and Machine Learning – ICANN 2018

Verlag: Springer International Publishing

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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.

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Metadaten
Titel
A Deep Learning Approach for Sentence Classification of Scientific Abstracts
verfasst von
Sérgio Gonçalves
Paulo Cortez
Sérgio Moro
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-030-01424-7_47

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