Extracting Incidental and Global Knowledge through Compact Pattern Trees in Distributed Environment

This paper proposes to extract incidental and global knowledge through Compact Pattern Trees in a hierarchical structure through distributed and parallel computing paradigm. This method also facilitates privacy preserving with a minimal communication load. We present the experiments on different kinds of benchmark datasets for proposed mechanism.