  As the healthcare sector is facing major challenges, such as aging
populations, staff shortages, and common chronic diseases, delivering
high-quality care to individuals has become very difficult. Conversational
agents have shown to be a promising technology to alleviate some of these
issues. In the form of digital health assistants, they have the potential to
improve the everyday life of the elderly and chronically ill people. This
includes, for example, medication reminders, routine checks, or social
chit-chat. In addition, conversational agents can satisfy the fundamental need
of having access to information about daily news or local events, which enables
individuals to stay informed and connected with the world around them. However,
finding relevant news sources and navigating the plethora of news articles
available online can be overwhelming, particularly for those who may have
limited technological literacy or health-related impairments. To address this
challenge, we propose an innovative solution that combines knowledge graphs and
conversational agents for news search in assisted living. By leveraging graph
databases to semantically structure news data and implementing an intuitive
voice-based interface, our system can help care-dependent people to easily
discover relevant news articles and give personalized recommendations. We
explain our design choices, provide a system architecture, share insights of an
initial user test, and give an outlook on planned future work.
