The traditional frequent pattern mining algorithms generate an exponentially large number of patterns of which a substantial portion are not much significant for many data analysis endeavours. Due to this, the discovery of a small number of interesting patterns from the exponentially large number of frequent patterns according to a particular user\u27s interest is an important task. Existing works on patter
