Evaluating Ontology Modules Using an Entropy Inspired Metric

Paul Doran, V. Tamma, I. Palmisano, T. Payne, L. Iannone
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引用次数: 8

Abstract

In this paper we therefore propose a reformulation of the entropy metric to evaluate the amount of information carried by both the ontology structure, and also by the language elements (i.e. the semantics associated with the edges in the ontological graph). To evaluate this approach, the reformulated metric is empirically compared to Calemt & Daemi's original entropy metric, for a variety of different sized modules. The results suggest that not only can entropy differentiate between structurally different modules of the same size, but that our improved entropy metric provides a finer grain differentiation than the original entropy metric.
使用熵启发度量评估本体模块
因此,在本文中,我们提出了一种熵度量的重新表述,以评估本体结构和语言元素(即与本体论图中的边相关的语义)所携带的信息量。为了评估这种方法,对于各种不同大小的模块,将重新制定的度量与Calemt & Daemi的原始熵度量进行经验比较。结果表明,熵不仅可以区分相同尺寸的结构不同的模块,而且改进的熵度量提供了比原始熵度量更精细的晶粒区分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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