Recommender systems are efficient tools for filtering online information, which is
widespread owing to the changing habits of computer users, personalization trends, and …

This paper reviews the research trends that link the advanced technical aspects of
recommendation systems that are used in various service areas and the business aspects of …

The rapid growth and use of artificial intelligence (AI)-based systems have raised concerns
regarding explainability. Recent studies have discussed the emerging demand for …

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 …

Today, users are surrounded by many items. Recommender Systems are used to help users
find items of interest. Collaborative Filtering is one of the most successful techniques of …

This paper presents a novel genetic-based recommender system (BLI GA) that depends on
the semantic information and historical rating data. The main contribution of this research …

In recent years, internet technologies and its rapid growth have created a paradigm of digital
services. In this new digital world, users suffer due to the information overload problem and …

Recommender systems are information filtering tools that aspire to predict the rating for
users and items, predominantly from big data to recommend their likes. Movie …

With the eruption of big data, practical recommendation schemes are now very important in
various fields, including e-commerce, social networks, and a number of web-based services …

Over the last decade, there has been a burgeoning of data due to social media, e-commerce
and overall digitisation of enterprises. The data is exploited to make informed choices …