一种关系数据库中基于云模型关联规则的提取

为了发现有效的关联规则，属性在比较高的水平被范化，允许相邻属性值或者语言项的重量．这种软划分可以映射人类的想法，同时使发现的知识鲁棒．利用云模型的理论与方法求解数量关联问题，给出了一种云关联规则的定义，并提出了基于云模型理论支持度和置信度的计算方法，最后提出了一种提取算法Cloud model A．这种方法较好地软化了数量属性论域的划分边界，从而使得挖掘出的云关联规则更容易被人理解。

An Algorithm of Mining Association Rules Based on Cloud Model in Relational Databases

In order to discover strong association rules, attribute values are generalized at higher concept levels, allowing overlapping between neighbor attribute values or linguistic terms.And this kind of soft partitioning can mimic human being's thinking, while making the discovered knowledge robust.The article proposed an approach for mining quantitative association rules.It gave the definition of the cloud model association rules and presented an algorithm of support and confidence based on cloud model, at last, presented an efficient algorithm Cloud Model A. The method can well soften the domain partition boundary of the quantitative attributes, so the cloud association rules can be easily understood.