A semantic approach to recognize behaviours in teenagers Gianfranco E. Modoni gianfranco.modoni@itia.cnr.it Institute of Industrial Technologies and Automation - National Research Council, Bari, Italy Marco Sacco marco.sacco@itia.cnr.it Institute of Industrial Technologies and Automation - National Research Council, Milano, Italy Gabriela Candea gabriela.candea@ropardo.ro Ropardo S.R.L., Sibiu, Romania Silvia Orte silvia.orte@eurecat.org Eurecat, Barcelona, Spain Filip Velickovski filip.velickovski@eurecat.org Eurecat, Barcelona, Spain Keywords Semantic Web Context awareness Semantic Repository Behaviour recognition Abstract This research aims to realize a knowledge-based system recognizing teenagers’ behaviours in the lifestyle domain. Since various heterogeneous data sources are involved in this recognition process (e.g. wearable sensors, etc.), it is essential to face the harmonization of the data produced from these disparate sources and expressed under the form of both structured and unstructured content. The herein proposed approach leverages a common semantic reference model which represents the individual as a whole, permitting classification and integration of behavioural and contextual information. In this regard, an automatic semantic enrichment of the data produced by the involved sources is carried out, thus allowing to support a behaviour recognition process handled in a two-phase process (real-time and long-term detection and analysis of behaviours and trends). 1. Introduction Presently we are witnessing a growing demand of customized services which are tailored to the specific needs and characteristics of users. A key success factor for the implementation of these services is the user profiling, which consists of creating an explicit representation of a person's identity, i.e., a conceptual understanding of the user [1] [2] that is commonly employed to enhance usability as well as to support personalization, adaptivity and other user-centric features [3] . In addition, as a user might be found in various contexts, it is essential to construct a conceptual representation of a user model which is context-aware, thus able to infer which context the user is in a given moment in time, and consequently adapts the intervention to the selected context. This paper reports major features of an approach to support the process of user profiling which leverages the combination of Semantic Web technologies (SWT) [4] with the mobile and wearable technologies. The potential of this approach has been verified in the context of the European research project PEGASO [5] which aimed at promoting healthy lifestyle among teenagers. In particular, it provides personalized interventions based on the recognition of users’ behaviours with the objective of triggering an adjustable behaviour change process. In this regard, an ontology-based approach (Fig. 1) [6] is adopted to capture and cover the knowledge related with the so called Virtual Individual Model (VIM) [7] , characterizing the user on 1