User Ontology for Intelligent Decision Support Based on User Digital Life

Abstract

The research is aimed at the development of an ontology that classifies the users into user types based on which personalized decisions are recommended. A user type represents a category of users distinguished by common preferences and decision-making behaviours. The ontology is intended to be used in a decision support system implemented following an earlier proposed conceptual framework of intelligent decision support based on user digital life. The paper briefly introduces this framework and provides the formalization for main framework components. The major research result is a multi-aspect user ontology that models a user via three aspects: user profile, user segment, and user digital life model. Users’ digital traces is the framework’s component that provides information about the users to determine their types. Suggestions on ontology usage for intelligent decision recommendation are provided.