A user's feedback ontology for context-aware interaction

The diversity of interactions flows offers a large amount of information that can contribute significantly the interaction context-awareness at runtime. Particularly, users interventions can indicate accurately user's preferences and needs and can improve the personalization process. User's feedback looks promising to provide knowledge and assessment for an effective adaptation performance. However, there is no any agreed terminology for gathering and assuring the full understanding of what "Feedback" represent for adaptation, what is the added value? What it entails and how it could be interpreted. In this paper, we propose an extensible feedback ontology focusing upon the multidimensional nature of feedback and addressing the runtime personalization process.