# A Deep Neural Network Sentence Level Classification Method with Context Information

arXiv: https://arxiv.org/abs/1809.00934 · HTML: https://mlsanity.com/paper/1809.00934/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Aug 2018.

## Built on by (most cited first, 1 of 1)

- [Analyzing Vietnamese Legal Questions Using Deep Neural Networks with Biaffine Classifiers](https://mlsanity.com/paper/2304.14447/) (2023)

## Abstract (arXiv)

In the sentence classification task, context formed from sentences adjacent to the sentence being classified can provide important information for classification. This context is, however, often ignored. Where methods do make use of context, only small amounts are considered, making it difficult to scale. We present a new method for sentence classification, Context-LSTM-CNN, that makes use of potentially large contexts. The method also utilizes long-range dependencies within the sentence being classified, using an LSTM, and short-span features, using a stacked CNN. Our experiments demonstrate that this approach consistently improves over previous methods on two different datasets.