A genetic algorithm (GA) is an evolutionary algorithm inspired by the natural selection and
biological processes of reproduction of the fittest individual. GA is one of the most popular …

Cold Start problems in recommender systems pose various challenges in the adoption and
use of recommender systems, especially for new item uptake and new user engagement …

Recently, recommender systems have played an increasingly important role in a wide
variety of commercial applications to help users find favourite products. Research in the …

Collaborative filtering (CF) is a widely applied method to perform recommendation tasks in a
wide range of domains and applications. Dictionary learning (DL) models, which are highly …

Recommender systems'(RSs) research has mostly focused on algorithms aimed at
improving platform owners' revenues and user's satisfaction. However, RSs have additional …

Due to the huge expand in global markets and financial transactions, the importance of E-
commerce has grown significantly, so to achieve fully functioning, scalable, reliable, efficient …

The focus of the present study is to present a stochastic numerical computing framework
based on Gudermannian neural networks (GNNs) together with the global and local search …

The recommendation problem involves the prediction of a set of items that maximize the
utility for users. Numerous factors, such as the filtering method and similarity measure, affect …

Recently, there is difficulty in extracting useful information from huge online information due
to the rapid growth of the internet. Therefore, the Recommendation system (RS) is needed …

Through the Internet, learners can access available information on e-learning platforms to
facilitate their studies or to acquire new skills. However, finding the right information for their …