Model-Based Approach to Design and Develop Usable and Dependable Recommender Systems

Large companies rely on recommender systems to support users' processes of decision-making and analysis of large datasets of items. In critical context, such as civil aircraft cockpit, recommender systems can be a powerful tool for operators to support their tasks. Operators can be confronted with choosing the right option depending on the current alerts and context from a set of alternatives. The main goal of the presented PhD is to propose a model-based approach for the design and the development of dependable and usable recommender systems. This paper elaborates on challenges and approaches for engineering dependable and usable recommender systems.