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Emerging patterns (EPs) are those item sets whose supports change significantly from one class to another. Studies have shown that they have very powerful distinguishing features and are very useful for constructing accurate classifiers. The task of finding such patterns is a challenging problem and efficient techniques for their mining are needed. Precious EP mining approaches often produce a large number of EPs, which makes it very difficult to choose interesting ones manually. In this paper, the authors propose a particular type of emerging patterns called shared emerging patterns. The authors also present a new tree based algorithm for their efficient discovery. The basis of the algorithm is the construction of trees whose structure specifically targets the likely distribution of emerging patterns. Experiment results show that the algorithm has a good performance.