  Recently Convolutional Neural Networks (CNNs) models have proven remarkable
results for text classification and sentiment analysis. In this paper, we
present our approach on the task of classifying business reviews using word
embeddings on a large-scale dataset provided by Yelp: Yelp 2017 challenge
dataset. We compare word-based CNN using several pre-trained word embeddings
and end-to-end vector representations for text reviews classification. We
conduct several experiments to capture the semantic relationship between
business reviews and we use deep learning techniques that prove that the
obtained results are competitive with traditional methods.
