[PDF] Top 20 Rationale Augmented Convolutional Neural Networks for Text Classification
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Rationale Augmented Convolutional Neural Networks for Text Classification
... We used a collection Risk of Bias (RoB) text classifi- cation datasets, described at length elsewhere (Mar- shall et al., 2016). Briefly, the task concerns as- sessing the reliability of the evidence presented in ... See full document
10
Khmer handwritten text recognition with Convolution Neural Networks
... different convolutional networks have been trained and their performance has been ...based classification based on full feature set, as well as classification based on FS with Gabor filters, ... See full document
6
Graph Convolutional Networks for Text Classification
... Text classification is an important and classical problem in natural language ...applied convolutional neural networks (convolu- tion on regular grid, ...graph convolutional ... See full document
8
Clinical text classification with rule-based features and knowledge-guided convolutional neural networks
... lutional Networks (GCN) to classify the semantic rela- tions between medical concepts in discharge summaries from the i2b2-VA challenge dataset [24] and showed that CNN, RNN and GCN with only word embedding ... See full document
9
Sentiment Classification Via Recurrent Convolutional Neural Networks
... Recurrent Neural Network (RecurrentNN). This model uses a word to analyze a text word, and it stores all the previous text semantics in the hidden layer of a fixed ...the Convolutional ... See full document
9
Hierarchical Convolutional Attention Networks for Text Classification
... Text classification is an important research area in natural language processing ...Traditional text classification approaches utilize features gen- erated from vector space models such as ... See full document
13
Very Deep Convolutional Networks for Text Classification
... shallow neural net was proposed in (Kim, 2014): one convolutional layer (using multiple widths and filters) followed by a max pooling layer over ...six convolutional layers, followed by three fully ... See full document
10
Sequential Short Text Classification with Recurrent and Convolutional Neural Networks
... short-text classification, we introduce a model based on recurrent neural net- works (RNNs) and CNNs for sequential short-text classification, and evaluate it on the dialog act classi- ... See full document
6
Inter-Class Angular Loss for Convolutional Neural Networks
... Baseline Networks To show the adaptability of ICAL to different networks with different classification tasks, we apply ICAL to two types of convolutional neural networks (CNNs) ... See full document
8
Hierarchical Classification with Convolutional Neural Networks for Biomedical Literature
... relation classification [12], and Dos Santos utilized CNNs for semantic analysis of text ...document, Convolutional Neural Network consists of convolution layers, ReLU and k-max pooling ... See full document
9
Atrial fibrillation classification based on convolutional neural networks
... tional neural networks for diagnosing ...30 convolutional neural networks were applied and com- pared in this study for the diagnosis of the normal sinus rhythm (NSR) ...Alex ... See full document
6
Combining Recurrent and Convolutional Neural Networks for Relation Classification
... Due to the repetition of the middle context, we force the network to pay special attention to it. The two contexts are processed by two independent convo- lutional and max-pooling layers. After pooling, the results are ... See full document
6
Short Text Clustering via Convolutional Neural Networks
... learn text representation from raw text ...embedding, neural networks demonstrate their great performance in terms of constructing text represen- tation, such as Recursive Neural ... See full document
8
A Sensitivity Analysis of (and Practitioners’ Guide to) Convolutional Neural Networks for Sentence Classification
... for text classification will undoubtedly continue to be developed, those deploying such technolo- gies in practice will likely be attracted to simpler variants, which afford fast training and prediction ... See full document
11
Cancer Hallmark Text Classification Using Convolutional Neural Networks
... of convolutional neural networks to the biomedical do- main text classification task of identifying the hallmarks of cancer associated with publication ...document text and word ... See full document
9
Understanding Convolutional Neural Networks for Text Classification
... We present an analysis into the inner workings of Convolutional Neural Networks (CNNs) for processing text. CNNs used for computer vi- sion can be interpreted by projecting filters into image ... See full document
10
Unified Framework For Deep Learning Based Text Classification
... artificial neural networks, which are inspired by biological brain model made of ...are convolutional neural network (CNN), deep belief networks, recurrent neural networks ... See full document
5
Brain Tumor Classification Using Convolutional Neural Networks
... tumor classification with high accuracy, performance and low ...tumor classification is performed by using Fuzzy C Means (FCM) based segmentation, texture and shape feature extraction and SVM and DNN based ... See full document
5
Convolutional Neural Networks for Sentence Classification
... In the present work we have described a series of experiments with convolutional neural networks built on top of word2vec. Despite little tuning of hyperparameters, a simple CNN with one layer of ... See full document
6
Deep Pyramid Convolutional Neural Networks for Text Categorization
... deep convolutional neural net- work (CNN) architecture for text catego- rization that can efficiently represent long- range associations in ...complex neural networks have been proposed ... See full document
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