A User Interface Concept for Context-Aware Recommender Systems

Abstract

A context-aware recommender system incorporates the knowledge of different contextual factors - such as time or weather information - to improve the item suggestions made to a user. While this provides great benefit to users, it might be hard for them to grasp why certain items are relevant, given the complexity of a context-aware recommender. In this paper, we propose, implement and evaluate a user interface concept that seeks to tackle this challenge. We show how popularity graphs can be used to inform the user about the relevance of items in different contexts and how users perceive different contextual factors given our concept. A user study with 14 participants demonstrates that our concept is valid and appreciated by users.