… deep learning techniques in the CF context for latent factor modelling. In this research,
authors … a systematic review focusing on state-of-the-art literature on deep learning techniques …

… on the state-of-the-art deep learning-based RS which include the application domains,
datasets and different metrics used for evaluating the performance of the deep learning-based …

… overview of the state-of-the-art in reinforcement learning based recommender systems (RLRSs). …
In this section, we present RL-based RSs; ie, methods that do not use deep learning for …

… We propose a novel deep learning hybrid recommender system to address the gaps in
Collaborative Filtering systems and achieve the state-of-the-art predictive accuracy using …

… Recently, the application of deep learning in recommender systems have been frequently
… recommendation algorithm with a state-of-the-art multi-criteria CF recommendation methods …

… of state-of-the-art AI in recommender systems … deep learning-based recommender systems
according to the different types of deep neural networks applied in recommender systems. …

… The literature related to these techniques mentioning their ability … Recommendation System
are presented in this survey. The … recommendation techniques or use machine learning …

… In the following, we focus on most recent state-of-the-art research, but we start with a … with
handcrafted features, the advantage over deep learning approaches is that recommendations …

… , and includes more than 20 state-of-the-art SSR methods. Through rigorous experiments …
tion models, have been extensively covered in previous surveys on deep learning [8], [40] and …

… Recommender system is one of the most important … graph neural networks have become
the new state-of-the-art … a very recent survey on deep learning-based recommender systems. It …