数据挖掘方法本体研究

Research on Ontology of Data Mining Methods

数据挖掘是包含多个阶段的知识发现过程。一个简单、但典型的数据挖掘过程可能包括数据预处理阶段,数据挖掘算法的应用阶段,以及对挖掘结果的可视化处理阶段。在每个阶段,都会有多个算法或方法供数据挖掘工作者选择,但仅有一些算法和方法组合是有效的。即使是数据挖掘领域的专家,也可能会忽略一些重要的、有助于知识发现的数据挖掘算法或方法。本文中,我们将讨论使用本体的方法来协助数据挖掘工作者在实施数据挖掘过程中对众多可供选择的算法和方法进行选择。

A data mining(DM)process involves multiple stages. A simple, but typical, process might include prepro- cessing data, applying a data-mining algorithm, and visualizing the mining results. There are many possible choices for each stage, and only some combinations are valid. Therefore, both novices and data-mining specicalists could overlook some important, potentially fruitful optionos. In this paper, we introduce how to create the ontology of data mining methods in order to facilitate the choice of DM processes to execute.