概念近似方法的比较评价

J. Deogun, Liying Jiang
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引用次数: 5

摘要

形式概念分析(FCA)是一种从数据中推导出概念结构的方法,这些数据被表示为具有特征的对象。FCA根据对象和特征之间的关系发现数据中的依赖关系。然而,并不是每一对对象和特征都定义了一个概念。概念近似是找到最好的或最接近的概念来近似一对对象和特征。概念近似的意义在于,在我们找不到一个概念的情况下,使用概念近似可以给出最佳或最可能的解。本文通过实验对三种方法在文献检索中的应用进行了评价。我们对这些方法进行分析,并给出结论。
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Comparative evaluation on concept approximation approaches
Formal concept analysis (FCA) is a method for deriving conceptual structures out of data that are represented as objects with features. FCA discovers dependencies within the data based on the relation among objects and features. However, not every pair of objects and features defines a concept. Concept approximation is to find the best or closest concept(s) to approximate a pair of objects and features. Concept approximation is significant in that under the circumstances that we can not find a concept, using concept approximation will give the best or most possible solution. In this paper, we evaluate three approaches through experiments in the application of document retrieval. We provide analysis of these approaches and give our concluding remarks.
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