面向属性的量化归纳

数据简化是数据库中知识发现的一个重要研究方向。面向属性的归纳（AOG）可以用于数据简化。首先从数据简化的角度分析讨论了AOG及其不足；AOG的单一属性阈值控制是布尔型控制，在有例外存在的情况下，可能造成数据过度简化，失去数据简化的意义。其次在AOG的基础上提出了面向属性的量化归纳（QAOG）以弥补AOG的不足；引入记录阈值的概念，用属性阈值和记录阈值同时进行控制，使控制从布尔型变成数量型，对没有例外存在的情况产生与AOG相同的效果，而对有例外存在的情况产生比AOG更好的效果，还给出了一个有效的QAOG算法。

QUANTIFIABLE ATTRIBUTE ORIENTED GENERALIZATION

Data reduction is one of the important topics in knowledge discovery in databases. Attribute oriented generalization (AOG) can be used in data reduction. First, AOG and its shortcomings are discussed from the view of data reduction: the single attribute threshold control of AOG is boolean control, so when there are exceptions, it can cause data over reduction and lose the meanings of data reduction. Then, quantifiable attribute oriented generalization (QAOG) based on AOG is presented in order to develop AOG: record threshold is introduced; attribute threshold and record threshold are used simultaneously in order to change boolean control to quantifiable control, so when there is no exception, it has the same results as AOG, otherwise, it has better results than AOG. An efficient algorithm of QAOG is also given.