With the recent development of online transactions, recommender systems have
increasingly attracted attention in various domains. The recommender system supports the …

The advancement in technology accelerated and opened availability of various alternatives
to make a choice in every domain. In the era of big data it is a tedious and time consuming …

Recommender systems are effective tools of information filtering that are prevalent due to
increasing access to the Internet, personalization trends, and changing habits of computer …

In recent years, deep learning's revolutionary advances in speech recognition, image
analysis, and natural language processing have gained significant attention. Deep learning …

With the growing volume of online information, recommender systems have been an
effective strategy to overcome information overload. The utility of recommender systems …

Recommender systems have been in existence everywhere with most of them using single
ratings in prediction. However, multi-criteria predictions have been proved to be more …

Recommender systems are known as intelligent systems which have many applications in
enormous domains such as social networks, e-commerce services, and online shopping …

Easy internet access and technological advancements have resulted in information overload
and a plethora of options, making decision-making extremely difficult. Recommender …

Due to the widespread availability of implicit feedback (eg, clicks and purchases), some
researchers have endeavored to design recommender systems based on implicit feedback …

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 …