  Predictive analytics over mobility data are of great importance since they
can assist an analyst to predict events, such as collisions, encounters,
traffic jams, etc. A typical example of such analytics is future location
prediction, where the goal is to predict the future location of a moving
object,given a look-ahead time. What is even more challenging is being able to
accurately predict collective behavioural patterns of movement, such as
co-movement patterns. In this paper, we provide an accurate solution to the
problem of Online Prediction of Co-movement Patterns. In more detail, we split
the original problem into two sub-problems, namely Future Location Prediction
and Evolving Cluster Detection. Furthermore, in order to be able to calculate
the accuracy of our solution, we propose a co-movement pattern similarity
measure, which facilitates us to match the predicted clusters with the actual
ones. Finally, the accuracy of our solution is demonstrated experimentally over
a real dataset from the maritime domain.
