Abstract In the era of internet access, recommender systems try to alleviate difficulty consumers face while trying find items (e.g. services, products, or information) that better match their needs. To do so, a system selects and proposes (possibly unknown) may be interest some candidate consumer, by predicting her/his preference for this item. Given diversity needs between enormous variety re...

The most common way to listen recorded music nowadays is via streaming platforms which provide access tens of millions tracks. To assist users in effectively browsing these large catalogs, the integration Music Recommender Systems (MRSs) has become essential. Current real-world MRSs are often quite complex and optimized for recommendation accuracy. They combine several building blocks based on ...

The origins of modern recommender systems date back to the early 1990s when they were mainly applied experimentally personal email and information filtering. Today, 30 years later, personalized recommendations are ubiquitous research in this highly successful application area AI is flourishing more than ever. Much last decades was fueled by advances machine learning technology. However, buildin...

the rapid growth of world wide web has affected the nature of interactions between customers and companies enormously. one significant consequence of this phenomenon is definitely the emergence and development of e-commerce websites and online stores all over the web. in spite of its great benefits, online shopping could turn into a complicated procedure from the customer point of view. in most...