Offer #2018.35

Attention Management for Mobile Apps

Faculty of Computer and Information Science, University of Ljubljana, Slovenia

The problem/challenge

An app, e.g. news delivery similar to Flipboard, has certain news headlines it wants to deliver to a user. The problem is to identify the best times where the user is interruptible (e.g. not in a meeting, not sleeping, not driving a car, etc.). Compared to random sending, notification delivery at "interruptible" times reduces user frustration and increases click rate.

The invention/product

The Mobile Attention Management solutions is application oblivious. As a user goes about her daily routine, our module senses the context (e.g. location, physical activity, time of day, etc.) and finds moments when a user is likely to click on a delivered notification and manages notification delivery accordingly. The feedback on the reaction (i.e. clicked or not) is used to refine the underlying models, so in future our module makes more accurate predictions. More info at:

Companies/industry we are looking for

We are looking for companies who are trying to:

  • Increase user engagement in their mobile application
  • Reduce user frustration and lower churn rate of their mobile app
  • Delivering personalized information to users in a timely fashion (for instance, in mHealth, behavior change interventions, etc.)
Next steps/Activities

We are interested in partnering with serious industrial players in order to increase real-world impact and expand the application domains in which our solutions are trialed. We have more than six years of experience in smart notification scheduling, user behavior modeling, and mobile interaction analysis research. Our solutions range from highly innovative physiological signal sensing of a user's attention to ready-to-use open source software for Android notification management. More info about our research at:

Make an enquiry

Date published12/18/2018StatusLooking for collaborationTechnology areasHuman-Machine InteractionLocation Based TechnologiesMachine LearningMarket IntelligenceMedical and Health ApplicationsWeb and Mobile Applications