发现频繁的项目集，包括罕见项在内的问题，已引起广泛关注。采矿过程需要足够灵活同时提取频繁的和罕见的规则物。在另一方面，最近已经表明约束编程是一个灵活的方式去处理数据挖掘任务的一个灵活方式。在本文中，我们为具有多个最小支持的采矿项目集提出了约束编程方法。我们的方法在最小项目集支持上为使用者提供表达任何一种约束的可能性。实验分析表明与最先进的技术相比我们的方法的实际有效性。
原文题目：Frequent Itemset Mining with Multiple Minimum Supports: a Constraint-based Approach
原文：The problem of discovering frequent itemsets including rare ones has received a great deal of attention. The mining process needs to be flexible enough to extract frequent and rare regularities at once. On the other hand, it has recently been shown that constraint programming is a flexible way to tackle data mining tasks. In this paper, we propose a constraint programming approach for mining itemsets with multiple minimum supports. Our approach provides the user with the possibility to express any kind of constraints on the minimum item supports. An experimental analysis shows the practical effectiveness of our approach compared to the state of the art.
具有多个最小支持频繁的项目表挖掘：基于约束的方法.pdf