May 1, 2022 · Deep neural network models, including convolutional neural networks (CNN) and recurrent neural networks (RNN), yield promising results on text classification tasks. RNN …

Nov 12, 2019 · The feature fusion model is divided into a multiple attention (MATT) CNN model and a bi-directional gated recurrent unit (BiGRU) model. The CNN model inputs the word …

Nov 22, 2018 · According to the observation that a word with higher score carries more valuable information in sentence modeling, this paper presents a novel low-complexity model termed as …

Aug 25, 2014 · We report on a series of experiments with convolutional neural networks (CNN) trained on top of pre-trained word vectors for sentence-level classification tasks. We show that …

A CNN BiLSTM is a hybrid bidirectional LSTM and CNN architecture. In the original formulation applied to named entity recognition, it learns both character-level and word-level features. The …

Nov 24, 2018 · The model uses bidirectional LSTM (Bi-LSTM) to build the memory of the sentence, and then CNN is applied to extracting attention from memory to get the attentive …

new unified architecture including CNN, BiLSTM attention mechanism and convolution layer, which is called attention-based bidirectional long-term memory convolution layer (AC-BiLSTM).

May 26, 2020 · In this paper, we demonstrate and generalize a model combining bi-directional long short term memory (LSTM) and convolutional neural network (CNN), as bi-directional …

the sentence classification model, CNNs for NLP showed unique results[12]. RNN is a major fundamental model of deep learning, Mikolov et al. presented in 2010 a method of performing …

May 31, 2018 · They achieve state-of-the-art performance superior to simple (Bi-)LSTM and CNN approaches. The authors conduct further experiments varying three of their hyperparameters: …