Sentiment based hybrid deep learning for recommender models
Lamia Berkani, Ilyes Djerfaf, Mouaadh Hamed Abdelouahab · 2023
To solve the data sparsity problem, we propose in this article an approach based on hybrid deep learning sentiment model, using Recurrent Neural Networks (RNN) or Convolutional Neural Networks (CNN) with Long Short-Term Memory (LSTM). The word embeddings Glove and Word2Vec were exploited in the RNN-LSTM and CNN-LSTM hybrid combinations. The results of experiments on two datasets from the Amazon database show that our approach significantly outperforms state-of-the-art recommendation models.