摘要： 概念层次是目前数据挖掘和知识发现的前沿性方法。为了把概念层次用于数据挖掘，需要解决如何从现有数据集自动生成概念层次，如何存储和处理网状概念层次结构及如何提高概念层次结构的搜索效率等问题。文章提出适用于任何数据挖掘功能的通用编码方法――基于层次域的概念层次实数编码法，该方法有效地解决了概念层次的存储和检索问题，并在微机电系统领域进行了与典型算法的对比分析。

关键词: 概念层次；编码算法；数据挖掘

Abstract: As one of the useful background knowledge, concept hierarchies organize data or concepts in hierarchical forms or in certain partial order, which are used for expressing knowledge in concise, high-level terms, and facilitating mining knowledge at multiple levels of abstraction. To incorporate the concept hierarchies into a data mining system, encoding plays a key role. A novel generic encoding algorithm is proposed which can be treated as a generic purpose encoding strategy suitable for any data mining functionalities. The partial order of the hierarchy is exactly represented by the codes so that it only needs to manipulate the codes when processing mining tasks.

Key words: Concept hierarchy; Encoding algorithm; Data mining