Summary: Accurate Temporal Relationships in Sequences
of User Behaviours in Intelligent Environments
Asier Aztiria and Juan Carlos Augusto and Rosa Basagoiti and Alberto Izaguirre
Abstract Intelligent Environments are supposed to act proactively anticipating
user's needs and preferences in order to provide effective support. Therefore, learn-
ing 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 discov-
ering accurate temporal relationships to define the relationships between actions of
Ambient Intelligence (AmI)    can be understood as `a digital environ-
ment that proactively, but sensibly, supports people in their daily lives' . Some
of the potential benefits that this technology can bring to people in their daily lives
include making an environment more comfortable, safer and more energy efficient.
In order to achieve these objectives, the environment should learn patterns of the
user which means that the environment has to gain knowledge about the prefer-
ences, needs and habits of the user in order to be in a better position to assist the
user adequately .
Let us consider the following scenario, which exemplifies a common behaviour