用神经网络选择多维数据挖掘空间的研究

多维数据挖掘是基于数据仓库系统的重要决策支持技术，遗憾的是，由于多维数据的复杂性使数据挖掘的效率和实用性都很差，本文通过对多维数据挖掘模型的分析，说明在多维数据挖掘过程中挖掘空间的选择是影响结果成败的关键步骤，在此基础上提出一种用于挖掘空间选择的神经网络模型，并通过实例应用说明该模型能够正确寻找到正确的挖掘空间，最后文章讨论了该模型的优缺点。

Locating Multi-Dimentioal Data Mining Space With Neural Networks

Multi dimentional data mining is an important technology of DSS basedof Data Warehouse, however, it's efficiency and utility is far from our expectation. This paper here, first, the significance of locating mining space correctly during the process of multi dimentional data mining is elucidated; then, a neural networks model for locating data mining space is proposed and a experimental result shows that this model can be used to locate the correct mining space; finally, the merits and demerits of this method is discussed.