【摘要】 数据网格作为面向服务的架构,为远程用户提供分布式数据查询、存储和管理等服务,而数据网格中的数据分类日益成为研究者们所关注的问题.本文描述了用于数据网格的一种高效的分类系统.该系统动态综合作为网格服务的多种分类方法(Dynamical Synthesis of Multiple Methods,DSMM),能够动态地改善传统分类方法的低准确率点,以负载平衡为前提将分类工作分布于网格中的各个结点上.另外,DSMM提供的生命周期管理保障了其作为一个网格应用的鲁棒性和灵活性,适合于网格的松耦合体系结构.实验采用了2927个乳腺癌患者病例,结果显示DSMM系统的确能够在数据网格环境中发挥其灵活性、高效性并提高分类的准确率.更多还原

【Abstract】 As a service oriented architecture,data grid provides distributed data access,storage and management for remote users.It has become growing concern among developers about the data classification issue in data grid environment.This paper proposes a high-efficient system used in data grid which makes dynamical synthesis of multiple methods(DSMM),distributes workloads to each node of the grid with the load-balance premise,and improves the low classification accuracy points of traditional methods.In spite of that,as an application in loose coupling grid environment,DSMM,which provides life time management of multiple classification methods,guarantees its robustness and flexibility.Experiment uses 2927 breast cancer cases and proves that the DSMM system has flexibility,high efficiency and increases the classification accuracy in data grid.更多还原