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Hierarchical Neural Networks for Sequential Sentence Classification in Medical Scientific Abstracts

2018-08-19 · EMNLP 2018 10 · Di Jin, Peter Szolovits

Prevalent models based on artificial neural network (ANN) for sentence classification often classify sentences in isolation without considering the context in which sentences appear. This hampers the traditional sentence classification approaches to the problem of sequential sentence classification, where structured prediction is needed for better overall classification performance. In this work, we present a hierarchical sequential labeling network to make use of the contextual information within surrounding sentences to help classify the current sentence. Our model outperforms the state-of-the-art results by 2%-3% on two benchmarking datasets for sequential sentence classification in medical scientific abstracts.

📄 PDF Abstract BibTeX arXiv:1808.06161

Code (1)

jind11/HSLN-Joint-Sentence-Classification 공식 구현 tf

Tasks

BenchmarkingClassificationGeneral ClassificationSentenceSentence ClassificationStructured Prediction

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