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The Weka4WS framework for distributed data mining in service-oriented Grids

机译:用于面向服务的网格中的分布式数据挖掘的Weka4WS框架

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摘要

The service-oriented architecture paradigm can be exploited for the implementation of data and knowledge-based applications in distributed environments. The Web services resource framework (WSRF) has recently emerged as the standard for the implementation of Grid services and applications. WSRF can be exploited for developing high-level services for distributed data mining applications. This paper describes Weka4WS, a framework that extends the widely used open source Weka toolkit to support distributed data mining on WSRF-enabled Grids. Weka4WS adopts the WSRF technology for running remote data mining algorithms and managing distributed computations. The Weka4WS user interface supports the execution of both local and remote data mining tasks. On every computing node, a WSRF-compliant Web service is used to expose all the data mining algorithms provided by the Weka library. The paper describes the design and implementation of Weka4WS using the WSRF libraries and services provided by Globus Toolkit 4. A performance analysis of Weka4WS for executing distributed data mining tasks in different network scenarios is presented.
机译:可以利用面向服务的体系结构范例在分布式环境中实现数据和基于知识的应用程序。 Web服务资源框架(WSRF)最近已经成为实现网格服务和应用程序的标准。可以利用WSRF为分布式数据挖掘应用程序开发高级服务。本文介绍了Weka4WS,它是一个框架,该框架扩展了广泛使用的开源Weka工具包,以支持启用WSRF的网格上的分布式数据挖掘。 Weka4WS采用WSRF技术来运行远程数据挖掘算法和管理分布式计算。 Weka4WS用户界面支持本地和远程数据挖掘任务的执行。在每个计算节点上,都使用符合WSRF的Web服务来公开Weka库提供的所有数据挖掘算法。本文使用Globus Toolkit 4提供的WSRF库和服务描述了Weka4WS的设计和实现。对Weka4WS的性能分析进行了介绍,该Weka4WS用于在不同的网络场景中执行分布式数据挖掘任务。

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