Nowadays, more and more news readers read news online where they have access to
millions of news articles from multiple sources. In order to help users find the right and …

In the literature, various collaborative filtering approaches have been developed to perform
an efficient recommendation on top of reducing the search cost of the customers. The …

Web recommender systems play a significant role in different domains, such as movies,
books, music, etc., and contributes to not only user satisfaction but also to e-business and e …

In the last ten years, social networks have had a great influence on people's lifestyles and
have changed, above all, the way users communicate and relate. This is why, one of the …

Abstract Information explosion creates dilemma in finding preferred products from the digital
marketplaces. Thus, it is challenging for online companies to develop an efficient …

Recommender systems are widely used on the Internet as tools for data analysis,
processing and discovery. Traditional recommendation algorithms mostly exploit rating …

In video recommendation, an ongoing effort is to satisfy users' personalized information
needs by leveraging their logged watch time. However, watch time prediction suffers from …

In this study, we describe a recommendation system for electronic books. The approach is
based on implicit feedback derived from user's interaction with electronic content. User's …

Recommender systems (RSs) play a very important role in web navigation, ensuring that the
users easily find the information they are looking for. Today's social networks contain a large …

The increasing popularity of O2O service make more and more people begin seeking and
booking services online. After that, they experience the services in brick-and-mortar stores …