scale data mining: Challenges and responses

Data mining over large data-sets is important due to its obvious commercial potential, However, it is also a major challenge due to its computational complex-ity. Exploiting the inherent parallelism of data mining algorithms provides a direct solution by utilising the large data retrieval and processing power of parallel architectures. In this paper, we present some results of our intensive research on paralielising data mining algorithms. In particular, we also present a methodol-ogy for determining the proper parallelisation strategy based on the idea of algorithmic skeletons and per-formance modelling. This research aims to provide a systematic way to develop parallel data mining algo-rithms and applications. ’ Parallelism in Data Mining Algorithms Numerous algorithms have been previously developed for data mining (Fayyad, Piatetsky-Shapiro, & Smyt