Researchers have widely acknowledged the potential of control mechanisms with which end-
users of recommender systems can better tailor recommendations. However, few e-learning …

Social media feeds are deeply personal spaces that reflect individual values and
preferences. However, top-down, platform-wide content algorithms can reduce users' sense …

Using personalized explanations to support recommendations has been shown to increase
trust and perceived quality. However, to actually obtain better recommendations, there …

There has recently been growing interest in the automatic generation of cooking recipes that
satisfy some form of dietary restrictions, thanks in part to the availability of online recipe data …

This work presents a playground platform to demonstrate and interactively explore a suite of
methods for utilizing user review texts to generate book recommendations. The focus is on …

The constant increase in the amount of data and information available on the Web has made
the development of systems that can support users in making relevant decisions …

Most online content platforms today are designed to maximize the time users spend
engaging with their content. This engagement allows platforms to both serve advertisements …

Artificial intelligence and machine learning algorithms have become ubiquitous. Although
they offer a wide range of benefits, their adoption in decision-critical fields is limited by their …

Providing explanations for recommended items allows users to refine the recommendations
by critiquing parts of the explanations. As a result of revisiting critiquing from the perspective …