Recommending Video Content for Use in Group-Based Reminiscence Therapy

Abstract

REMPAD is a semi-automated cloud-based system used to facilitate digital reminiscence therapy for patients with mild-to-moderate dementia, enacted in a group setting. REMPAD uses profiles for participants and groups to proactively recommend interactive video content from the Internet to match these profiles. In this chapter, we focus on the design of the system and then the system architecture, the system build, data curation, and usage scenarios. We also report a series of steps car- ried out as part of our user-centered design approach to system development, and a series of analyses on interaction logs which indicate various levels of effectiveness for different configurations of the recommendation algorithm we use. The results indicate high user satisfaction when using the system, and strong tendency towards repeated use in future.

Multidimensional Group Recommendations in the Health Domain

“…For groups there have been only a small amount of works. The authors of [47] focus on recommending video content in group-based reminiscence therapy. Besides this work, in our previous line of work, we focused on group recommendations in the health domain [9,10] by proposing a semantic similarity function that takes into account the patients medical profiles, showing its superiority over a traditional measure in group recommendations, and by introducing the notion of fairness [11], paving the way for our contribution in this paper.…”