Design of two combined health recommender systems for tailoring messages in a smoking cessation app
This work addresses smoking cessation for app users, but it is incremental as it applies existing recommender methods to a health domain without novel breakthroughs.
The authors tackled the problem of supporting smoking cessation by designing two recommender systems for a mobile app: a hybrid system to tailor health messages and a content-based system to schedule message delivery, with plans to assess performance in a pilot study.
In this article, we describe the design of two recommender systems (RS) designed to support the smoking cessation process through a mobile application. We plan to use a hybrid RS (content-based, utility-based, and demographic filtering) to tailor health recommendation messages, and a content-based RS to schedule a timely delivery of the message. We also define metrics that we will use to assess their performance, helping people quit smoking when we run the pilot.