… , a sentence similarity calculation model based on multi model … and evaluate the document
theme better. In this paper, the … The convolution neural network only includes convolution …

… counting and a contextual skip gram model. At the paraphrase identification level, the
authors apply a convolutional neural network model to learn more contextual and semantic …

… offered increased interpretability. A semi-supervised neural … The convolution operation plays
an essential role in … trained a convolutional neural network with one convolution layer that …

… the design of computing network security model based on … ’s NLP model based on the graph
convolutional neural network … design a better-performing NLP calculation method model to …

… enhance the classification performance. In this paper, a fast deep learning-based solution
model… In this paper, we propose a convolutional neural network (CNN) to extract features …

… sentence similarity, this study uses Sent2Vec, a sentence … input to the 1-dimension
convolutional neural network (1D-CNN) … model is better than the performance of other models and …

… Researchers observed that legitimate websites have a popularity of more than 100000 (lesser
is better; number 1 is Google) which will be our threshold. The rule will be based on this …

… While different deep neural networks are able to extract … neural networks using multi-view
classifiers to enhance the overall … paper is on using deep neural networks to extract features of …

… convolution neural network(CNN) is applied less than recurrent … a new model based on
RNN with CNN-based attention … However, our model not only performs better than early …

… The presentation layer uses BOW + deep neural network (DNN) to extract … improved methods
based on the Siamese network, proposes a semantic similarity calculation model based on …