模糊本体中的模糊相似度计算

Fuzzy Similarity Computation in Fuzzy Ontology

模糊本体作为不确定性知识表示模型,被广泛应用于计算机科学的各个领域;给出一种新模糊本体中模糊概念的模糊相似度计算方法;首先计算模糊本体图中边的模糊权重,从而得到模糊权矩阵;由正则经验模型计算模糊拉普拉斯矩阵次小特征值对应的特征向量,从而将模糊本体中的每个模糊概念映射到实直线,通过模糊概念对应实数之间的差值来得到它们的相对模糊相似度。

Fuzzy ontology, as a representation model for uncertain knowledge, is widely used in all fields in computer science. This paper gives a fuzzy similarity computation method for the fuzzy concept in a kind of fuzzy ontology, firstly by computing fuzzy weight of the edges of fuzzy ontology graphs to receive fuzzy weight matrix, then by using regular empirical model to calculate the eigenvector corresponding to the second smallest eigenvalue of fuzzy Laplacian matrix, then each fuzzy concept in fuzzy ontology is mapped to the real line, and the relative fuzzy similarity is obtained by the D-value between the corresponding real numbers of fuzzy concept.