The ongoing rapid expansion of the Internet greatly increases the necessity of effective
recommender systems for filtering the abundant information. Extensive research for …

Exploiting temporal context has been proved to be an effective approach to improve
recommendation performance, as shown, eg in the Netflix Prize competition. Time-aware …

Building a successful recommender system depends on understanding both the dimensions
of people's preferences as well as their dynamics. In certain domains, such as fashion …

“Nature shows us only the tail of the lion. But I do not doubt that the lion belongs to it even
though he cannot at once reveal himself because of his enormous size.”–Albert Einstein The …

Diversification has become one of the leading topics of recommender system research not
only as a way to solve the over-fitting problem but also an approach to increasing the quality …

What makes a good recommendation or good list of recommendations? Research into
recommender systems has traditionally focused on accuracy, in particular how closely the …

The Recommender Systems community is paying increasing attention to novelty and
diversity as key qualities beyond accuracy in real recommendation scenarios. Despite the …

More and more people read the news online, eg, by visiting the websites of their favorite
newspapers or by navigating the sites of news aggregators. However, the abundance of …

Personalized recommendations in search engines, social media and also in more traditional
media increasingly raise concerns over potentially negative consequences for diversity and …

Novelty and diversity have been identified, along with accuracy, as prominent properties of
useful recommendations. Considerable progress has been made in the field in terms of the …