基于本体关系的概念相似性直觉模糊集模型

Fa-Gui Liu, Fen Xiao, Yue-Dong Lin, Yang Zhang
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引用次数: 2

摘要

本体概念之间的语义相似性在服务发现和组合中起着重要的作用。本文利用本体关系,提出了一种新的直觉模糊集模型,利用三个不同权重的直觉模糊集对本体上的概念进行解释,并选择一个有效的相似度度量来计算概念相似度。该模型成功地将概念的所有语义信息转化为直觉模糊集的数学表达式,从而易于计算概念相似度。它不仅可以处理只呈现原子概念的简单本体论,还可以处理复杂的本体论,其中的概念可以从多个概念继承,并且与其他概念具有除is-a之外的语义关系。实验结果表明,该模型是有效的,且易于实现。
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An Intuitionistic Fuzzy Set Model for Concept Similarity Using Ontological Relations
Semantic similarity between ontological concepts plays an important role in service discovery and composition. In this paper, using the ontological relation, a novel intuitionistic fuzzy set model is proposed to interpret concepts on the ontology with three intuitionistic fuzzy sets of different weights, and an effective similarity measure of which is selected to calculate the concept similarity. The model successfully translates all the semantic information of a concept into mathematical expressions of intuitionistic fuzzy sets, thus concept similarity is easily calculated. It is designed to handle not only simple ontologies where only atomic concepts are presented, but also complex ones where concepts could inherit from multiple concepts and have semantic relations other than is-a with other concepts. The experimental result has shown that the model is effective, and it's easy to implement.
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