With the new era of the Internet, we have a large amount of data available in the form of
ratings, reviews, graphs, images, etc. However, still, people face difficulty in finding useful …

Purpose This study aims to provide a systematic review of the existing literature on the
applications of deep learning (DL) in hospitality, tourism and travel as well as an agenda for …

In Electronic commerce, customer reviews play a significant role in purchase making
decision. Most of the existing recommendation systems consider the customer reviews, user …

Recommender systems have become exceptionally widespread in recent years to deal with
the information overload problem by providing personalized recommendations. Multi-criteria …

In the modern world, where technology is at the forefront of every industry, there has been
an overload of information and data. Thus, a recommendation system comes in handy to …

This paper provides an innovative deep learning architecture to improve collaborative
filtering results in recommender systems. It exploits the potential of the reliability concept to …

Graph neural networks (GNNs), with their promising potential to learn effective graph
representation, have been widely used for recommender systems, in which the given graph …

The exponential outbreak of news articles makes it troublesome for the readers to find,
select and read the most relevant ones and alleviate the resulting information and cognitive …

The personalized recommendation system influences the recommendation of ideological
and political teaching resources in universities, resulting in a high MAE score. As a result …

Identifying user preferences is a complex operation, which makes its automa-tion
challenging, and existing recommendation systems that rely on one of the parameters …