Dominance Programming for Itemset Mining
Dominance Programming for Itemset Mining
复制标题
项集挖掘的优势编程
DOI：
10.1109/icdm.2013.92
复制
发表时间：
2013
期刊：
影响因子：
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通讯作者：
Siegfried Nijssen
中科院分区：
文献类型：
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作者：
Benjamin Négrevergne;Anton Dries;Tias Guns;Siegfried Nijssen
寻找一小组有趣的模式是模式挖掘中的一个重要挑战。在本文中，我们认为解决这一挑战的几种众所周知的方法都是基于在模式之间进行成对比较。示例包括查找闭合模式、自由模式、相关子组和天际线模式。尽管在每个问题上都取得了进展，但仍然缺乏解决这些问题（以及更多问题）的通用方法。本文解决了这一挑战。它提出了一种新颖的通用方法来处理涉及模式之间的成对比较的模式挖掘问题。我们的主要贡献如下。首先，我们提出了一种用于编程模式挖掘问题的新颖代数。该代数以一种新颖的方式将关系代数扩展到模式挖掘。它允许对各个模式的约束与模式之间的主导关系进行通用组合。其次，我们引入改进的通用约束满足系统来评估这些代数表达式。实验表明，这种通用方法确实可以有效地识别代数中表达的模式。
Finding small sets of interesting patterns is an important challenge in pattern mining. In this paper, we argue that several well-known approaches that address this challenge are based on performing pair wise comparisons between patterns. Examples include finding closed patterns, free patterns, relevant subgroups and skyline patterns. Although progress has been made on each of these individual problems, a generic approach for solving these problems (and more) is still lacking. This paper tackles this challenge. It proposes a novel, generic approach for handling pattern mining problems that involve pair wise comparisons between patterns. Our key contributions are the following. First, we propose a novel algebra for programming pattern mining problems. This algebra extends relational algebras in a novel way towards pattern mining. It allows for the generic combination of constraints on individual patterns with dominance relations between patterns. Second, we introduce a modified generic constraint satisfaction system to evaluate these algebraic expressions. Experiments show that this generic approach can indeed effectively identify patterns expressed in the algebra.