Emerging pattern mining is a data mining task that aims to discover discriminative patterns, which can describe emerging behavior with respect to a property of interest. In recent years, the description of datasets has become an interesting field due to the easy acquisition of knowledge by the experts. In this review, we will focus on the descriptive point of view of the task. We collect the existing approaches that have been proposed in the literature and group them together in a taxonomy in order to obtain a general vision of the task. A complete empirical study demonstrates the suitability of the approaches presented. This review also presents future trends and emerging prospects within pattern mining and the benefits of knowledge extracted from emerging patterns
