基于高性能云数据挖掘的算法研究

An Algorithm Research Based on High-performance Cloud Date Mining

论文设计并实现了一种可以用于存档、分析、和挖掘大型分布式数据集的高性能云。文中定义云为一种可以提供互联网资源与(或)服务的基础设施。存储云提供存储服务,计算云则提供计算服务。高性能且能保持这些服务自身的有效性和效率不变,自然很合理地被预期作为实现大规模数据挖掘的中间步骤。论文提出了一种使用Sector/Sphere框架和关联规则的云数据挖掘方法,同时给出了由Sphere计算云和关联规则支持的编程范例。

This paper describes the design and implementation of a high-performance cloud to archive, analyze and mine large distributed data sets. By a cloud, an infrastructure that provides resources and/or services over the Internet. A storage cloud provides storage services, while a compute cloud provides compute services. High-performance can be reasonably intended as a intermediate step of high-performance data mining activities over large-scale amounts of data, while still keeping unaltered the primary and self-contained focus of achieving effectiveness and efficiency in these task themselves. In this paper an algorithm is proposed to mine the data from the cloud using Sector/Sphere framework and association rules, and also describe the programming paradigm supported by the Sphere compute cloud and association rules.