Admire framework: Distributed data mining on data grid platforms

TL;DR

The paper introduces the ADMIRE framework, a new architecture designed for distributed data mining on heterogeneous data grid platforms, facilitating the development of scalable data mining techniques.

Contribution

It presents the ADMIRE architecture and interfaces, enabling efficient development and implementation of data mining applications on grid platforms.

Findings

Supports large, distributed, heterogeneous datasets

Provides user-friendly interfaces for data mining development

Compatible with platforms like Globus ToolKit and DGET

Abstract

In this paper, we present the ADMIRE architecture; a new framework for developing novel and innovative data mining techniques to deal with very large and distributed heterogeneous datasets in both commercial and academic applications. The main ADMIRE components are detailed as well as its interfaces allowing the user to efficiently develop and implement their data mining applications techniques on a Grid platform such as Globus ToolKit, DGET, etc.