Multi-Criteria Rating-Based Preference Elicitation in Health Recommender Systems


A multi-criteria rating looks for important dimensions to more extensively capture an individual’s opinion about a recommended item. Health Recommender Systems (HRS) is considered to be an emerging domain of recommender systems. In HRS, criteria for a multi-criteria preference elicitation of a recommendation have not yet been fully investigated to the best of our knowledge. In this paper, we investigate the criteria for the rating of a health promotion recommendation using an online survey. Drawing on both the relevant literature and the users’ responses, we came up with a list of 33 criteria that users are considering when they rate a health promotion recommendation. However, these criteria are not equally important to users. We discuss which of these criteria are more important in the users’ opinions. In short, our results show that users consistently consider effectiveness, emotional gain, and giving a good feeling as the most important criteria. Using the criteria derived from the literature, we came up with a model for the importance of the criteria which has three dimensions: effect, effort, and context. This study is the first step toward enhancing our understanding of HRS and the rating of a health promotion recommendation.

In Proceedings of the 3rd International Workshop on Health Recommender Systems co-located with the 12th ACM Conference on Recommender Systems (ACM RecSys 2018)
Helma Torkamaan

My research interests include Human-computer interaction, recommender systems, e-health and ubiqoutous computing.