Multi-criteria recommender systems have garnered considerable interests from researchers
and practitioners. In this paper, we study the optimization of the accuracy and scalability of …

Abstract A Multi-Criteria Recommender System (MCRS) represents users' preferences on
several factors of products and utilizes these preferences while making product …

Depending on the RMSE and sites sharing travel details, enormous reviews have been
posted day by day. In order to recognize potential target customers in a quick and effective …

Recommender systems enable users to deal with the information overload problem by
serving personalized predictions. Traditional recommendation techniques produce referrals …

The exponential increase in digital data has increased the amount of available online
information. This complicates the user's decision-making. Most online merchants and …

Collaborative filtering is specialized in suggesting appropriate products and services to the
users concerning personal characteristics and past preferences without requiring any effort …

Recommender systems provide their users an efficient way to handle information overload
problem by offering personalized suggestions. Traditional recommender systems are based …

Clonal selection algorithm and discrete Hopfield neural network are extensively employed
for solving higher-order optimization problems ranging from the constraint satisfaction …

While the tourism industry has grown rapidly in recent years, overtourism has become a
major problem at tourist destinations. One way of dealing with overtourism is to discover …

Traditional recommender system makes recommendations to users based on their
preferences by utilising overall ratings. However, these recommendations do not accurately …