Neural Networks for Joint Sentence Classification in Medical Paper Abstracts
Author(s)Dernoncourt, Franck; Lee, Ji Young; Szolovits, Peter
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Existing models based on artificial neural networks (ANNs) for sentence classification often do not incorporate the context in which sentences appear, and classify sentences individually. However, traditional sentence classification approaches have been shown to greatly benefit from jointly classifying subsequent sentences, such as with conditional random fields. In this work, we present an ANN architecture that combines the effectiveness of typical ANN models to classify sentences in isolation, with the strength of structured prediction. Our model outperforms the state-ofthe- art results on two different datasets for sequential sentence classification in medical abstracts.
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
Association for Computational Linguistics
Dernoncourt, Franck, et al. “Neural Networks for Joint Sentence Classification in Medical Paper Abstracts.” Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, April, 2019, Valencia, Spain, Association for Computational Linguistics, 2017: 694–700.