Anomaly detection is focused on identifying data objects that are different from our expectations. It can be influenced by bad practices like noise, errors, or some unexpected events. Unusual data points can be also due to rare, but correct behaviour, which often results in interesting findings, motivating a further investigation. For these reasons, it is necessary to develop some techniques that could allow us to identify such unusual events. We assume that such events may induce some objects generated by a ”different mechanism”, which indicates that these objects might contain unexpected patterns that do not conform to a normal behaviour.