Launched in 2016, the Health Recommender Systems Workshop (HealthRecSys) rapidly became a central forum for discussing the transformative capabilities of personalized recommender systems within the health and care sectors. Despite the unforeseen pause ...

Online news article recommendations are typically of the ‘more like this’ type, generated by similarity functions. Across three studies, we examined the representativeness of different similarity functions for news item retrieval, by comparing ...$\mathrm{}$$\mathrm{}$$\mathrm{}$

News media framing can shape public perception and potentially polarize views. Emotional language can exacerbate these framing effects, as a user’s emotional state can be an important contextual factor to use in news recommendation. Our research ...

News Recommender Systems (NRSs) have become increasingly pivotal in shaping the news landscape, particularly in how news is disseminated. This has also led to concerns about information diversity, especially regarding selective exposure in the realm of ...

Research in the recommender systems field typically applies a rather traditional evaluation methodology when assessing the quality of recommendations. This methodology heavily relies on incorporating different forms of user feedback (e.g., clicks) ...

In news media, recommender system technology faces several domain-specific challenges. The continuous stream of new content and users deems content-based recommendation strategies, based on similar-item retrieval, to remain popular. However, a ...

Applying AI techniques to journalism.

Multi-list recommender systems have become widespread in entertainment and e-commerce applications. Yet, extensive user evaluation research is missing. Since most content is optimized toward a user’s current preferences, this may be problematic in ...

Users of online recipe websites tend to prefer unhealthy foods. Their popularity undermines the healthiness of traditional food recommender systems, as many users lack nutritional knowledge to make informed food decisions. Moreover, the presented ...$\mathrm{}$$\mathrm{}$

Despite their proven various benefits, Recommender Systems can cause or amplify certain undesired effects. In this paper, we focus on Popularity Bias, i.e., the tendency of a recommender system to utilize the effect of recommending popular items to the ...

The workshop aims to discuss open problems, challenges, and innovative research approaches in the area of persuasive and behavior change recommender systems, that is, recommender systems aimed at modifying people's habits and behavior. Some questions ...

Predicting food preferences is challenging due to the numerous factors that can influence individual taste. Cultural influences are one such factor that can significantly impact food preferences. Irrespective of culture, however, food visual ...

• It is possible to predict food preferences using visual features of recipe images.
• Commonalities in cross-cultural visual food preferences can be identified.
• Low level visual features help to identify visual food preferences across ...

AI-powered symptom checkers are automating the work of telephone triage nurses in assessing patient urgency. Yet, these systems exclude several vulnerable patient groups and overlook telenurses’ competent interaction with their patients. This study, ...

Quality journalism has become more important than ever due to the need for quality and trustworthy media outlets that can provide accurate information to the public and help to address and counterbalance the wide and rapid spread of ...

The rapid growth of the volume and variety of online media content has made it increasingly challenging for users to discover fresh content that meets their particular needs and tastes. Recommender Systems are digital tools that support users in ...

Recommender systems have been put to use in the entertainment and e-commerce domains for decades, and in these decades, recommender systems have grown and matured into reliable and ubiquitous systems in today’s digital landscape. Relying on this ...

Food recommender systems show personalized recipes to users based on content liked previously. Despite their potential, often recommended (popular) recipes in previous studies have turned out to be unhealthy, negatively contributing to prevalent obesity ...

The widespread use of temporal aspects in user modeling indicates their importance, and their consideration showed to be highly effective in various domains related to user modeling, especially in recommender systems. Still, past and ongoing ...