基于关联规则和组合拓扑的概念挖掘

Albert Sutojo
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引用次数: 7

摘要

文档集中的概念集合可以用一种称为组合拓扑的简单复合体的几何结构来表示,其中每个关键字表示为一个顶点,关键字之间的关系表示为单纯形。由多个关键字组成的单纯形是高频关键字集。这些关键字在一个文档中出现得很近,在一组文档中也经常出现。这些关键词的高频率出现说明了关键词之间的关系。这些关系带有概念。这些关键字之间的关系可以通过关联规则挖掘捕获并表示为简单表。所有这些简单项的集合表示文档集中概念的结构。基于这种拓扑结构,对文档进行聚类,简单体的集合可以用作文档索引。
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Concept Mining using Association Rules and Combinatorial Topology
The collection of concepts in a document set can be represented by a geometric structure called simplicial complex of combinatorial topology where each keyword is represented as a vertex and the relation between keywords as simplex. A simplex which consists of more than one keyword is a high-frequency keywordset. These keywords occur close to each other within a document which also occur frequently within a set of documents. The high frequent occurrence of these keywords shows relations between keywords. These relations carry concepts. The relations of these keywords can be captured by association rule mining and represented as simplices. The collection of all these simplices, represents the structure of concepts within a document set. Based on this topology, documents are clustered and the collection of simplices can serve as document index.
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