Mar 12, 2016 · In this work, we present a model based on recurrent neural networks and convolutional neural networks that incorporates the preceding short texts.

Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks. Ji Young Lee, Franck Dernoncourt.

In this thesis, we propose several natural language processing methods based on artificial neural networks to facilitate the completion of systematic reviews.

In this thesis, we propose several natural language processing methods based on ar- tificial neural networks to facilitate the completion of systematic reviews.

In this thesis, we propose several natural language processing methods based on artificial neural networks to facilitate the completion of systematic reviews.

This thesis introduces several algorithms to perform sequential short-text classification, which outperform state-of-the-art algorithms and proposes several ...

In this work, we propose an improved sequence-based feature propagation scheme, which fully uses word representation and document-level word interaction.

In this work, we present a model based on recurrent neural networks and convolutional neural networks that incorporates the preceding short texts. Our model ...

This is my implementation of paper "Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks" in context of Dialogue act ...

Oct 5, 2021 · The first hidden layer in a neural network that classifies text is an embedding layer whose job is to convert padded sequences of word indices ...