Intelligent Environments are supposed to act proactively anticipating user's needs and preferences in order to provide effective support. Therefore, learning user's frequent behaviours is essential to provide such personalized services. In that sense, we have developed a system, which learns those frequent behaviours. Due to the complexity of the entire learning system, this paper will focus on discovering accurate temporal relationships to define the relationships between actions of the user.