When people receive advice while making difficult decisions, they often make better
decisions in the moment and also increase their knowledge in the process. However, such …

Background There has been growing attention towards personalizing dietary advice to the
specific lifestyle, phenotypic and genotypic properties of consumers. Consumer acceptance …

Multi-list recommender systems have become widespread in entertainment and e-
commerce applications. Yet, extensive user evaluation research is missing. Since most …

Content recommender systems often rely on modeling users' past behavioral data to provide
personalized recommendations-a practice that works well for suggesting more of the same …

Recent advances in the performance of machine learning algorithms have led to the
adoption of AI models in decision making contexts across various domains such as …

This paper considers unifying research on conversational user interfaces and recommender
systems. Studies on conversational user interfaces (CUIs) typically examine how …

Conversational agents (CAs) that deliver proactive interventions can benefit users by
reducing their cognitive workload and improving performance. However, little is known …

Choices and preferences of individuals are nowadays increasingly influenced by countless
inputs and recommendations provided by artificial intelligence-based systems. The accuracy …

Whereas many food recommender systems optimize for users' preferences, health is
another but often overlooked objective. This paper aims to recommend relevant recipes that …

Many food choices are made online. Interactive, personalized interfaces, such as
recommender systems, can help users to f! nd new products to eat or recipes to cook, but …