… an overview and summary for the state of the art; and (iii) we … horizons of deep learning-based
recommender systems research… for recommender systems and deep neural networks, and …

… intensely review applications of deep learning techniques applied in recommender systems
field to … The main factors that promote deep learning as the state-of-the-art machine learning …

… 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 …

… 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 …

… 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 …

… , and un-supervised learning. Experimental results show state-of-the-art performance using
deep learning when compared to traditional machine learning approaches in the fields of …

… 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. …

… 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 …

… 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 …