Multi-aspect user ontology for decision support based on digital traces

The paper presents a multi-aspect user ontology that classifies a decision maker into a group of users with common preferences and decision-making behaviors and allows the decision support system to prognosticate a recommending a decision based on the information about the preferences and behaviors of this group. The ontology relies upon the conceptual framework of intelligent decision support to make recommendations based on user digital traces and comprises three independent aspects: user profile, user segment, and model of user digital life, integration of which is supported by an upper ontology level.