In this study, a novel spatiotemporal graph convolutional networks model is proposed for
traffic flow prediction in urban road networks by fully considering an information geometry …

Sentiment Analysis has seen much progress in the past two decades. For the past few years,
neural network approaches, primarily RNNs and CNNs, have been the most successful for …

In the businesses, the sentiment analysis makes the brands understanding the sentiment of
their customers. They can know what people are saying, how they're saying it, and what they …

This study evaluates the performance of Recurrent Neural Network (RNN) and Transformer
models in replicating cross-language structural priming, a key indicator of abstract …

Neural networks, primarily recurrent and convolutional Neural networks, have been proven
successful in text classification. However, convolutional models could be limited when …

In the past few years, the growth of e-commerce and digital marketing in Vietnam has
generated a huge volume of opinionated data. Analyzing those data would provide …

Many machine learning tasks are structured as sequence modeling problems,
predominantly dealing with text and data with a time dimension. It is thus very important to …

Accurately forecasting traffic flow is crucial for the effective operation of intelligent
transportation systems (ITS), as it enables optimal resource allocation and efficient traffic …