Webservices oriented data mining in knowledge architecture

Massive parallelism is required for an efficient solution to data mining tasks, considering the proliferation of data and the need for high computational effort. The DisDaMin (Distributed Data Mining) project addressed distributed discovery and knowledge discovery through parallelization of data mining tasks. DisDaMin algorithms are based on the DG-ADAJ (Desktop-Grid Adaptive Application in Java), a middleware platform for Desktop Grid used as a deployment mechanism for DisDaMin algorithms. On the top of DG-ADAJ, SOA specific components could be employed to provide additional features and to improve current operation. An ESB (Enterprise Service Bus) built on the top of DG-ADAJ is going to provide improved availability, solve interoperability issues by exposing services through well established interfaces, and offer a loosely coupled infrastructure. An additional enactment layer is going to improve the performance of intelligent fragmentation of data, offering at the same time the necessary support for the execution of data workflows.

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