面向服务的分布式数据挖掘设计与实现

先进的应用持续产生非常大量有价值的数据,但是没有足够的技术来充分地抽取数据中潜在的知识.网格能为知识发现应用提供有效的计算支持.该文介绍了一个新颖的面向服务分布式高性能网格数据挖掘体系结构和设计原理.设计和实现了基于先进的Globus Toolkit 4和OGSA-DAI网格服务的分布式数据挖掘体系结构,并进一步用网格数据挖掘原型验证了该体系结构.

Design and Implementation of a Service-Oriented Distributed Data Mining

Advanced applications are continuing to generate ever larger amounts of valuable data,but we are in danger of being unable to extract fully the latent knowledge within the data because of insufficient technology.The grid can play a significant role in providing an effective computational support for knowledge discovery applications.This paper describes design principles and a service-oriented software architecture of a novel infrastructure for distributed and high-performance data mining in grid environments.This architecture is designed and being implemented on top of the Globus Toolkit 4(it provides basic grid services, such as authentication, information and resource management, etc.) and OGSA-DAI grid services(they provide basic access to grid databases).At last the architecture is validated through our prototype of the grid data mining.