网络用户隐私关心问题研究 个假设，得出不同用户对各项隐私程度关心程度的差异性，笔者采用关联分类的方式对数据进行了处理。? 关联分类(associative classification, AC)是一类新的面向决策表的规则获取技术，其核心思想是利用关联规则挖掘技术，通过频繁项集挖掘、决策规则生成
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Lazy associative classification 懒关联分类
fuzzy associative classification 模糊关联分类
Compared to the well-known associative classification algorithm of CBA, the proposed approach has the advantage of fast speed and high accuracy.
与同类关联分类方法（如CBA）比较，本文提出的方法具有学习速度快、 分类准确度高的优点。
Since the first algorithm of Classification Based on Association rules (CBA) was introduced in 1998, the algorithm design of associative classification and its application have been very active.
自1998 年出现第一个基于关联的分类算法（CBA）以来，关联分类算法的设计及应用研究一直非常活跃。
With a questionnaire survey, this paper investigates the personal information concerned by users and the concern level employing the statistical analysis and associative classification technology.
为此采用问卷调查的方式，利用统计分析和关联分类技术，对网络用户所关心的隐私信息及其关心程度进行研究。
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