Generalized Cases: Representation and Steps Towards Efficient Similarity Assessment
Generalized Cases: Representation and Steps Towards Efficient Similarity Assessment
复制标题
广义案例：高效相似性评估的表示和步骤
DOI：
10.1007/3-540-48238-5_16
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发表时间：
1999
期刊：
影响因子：
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通讯作者：
Ivo Vollrath
中科院分区：
文献类型：
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作者：
R. Bergmann;Ivo Vollrath
对于基于案例推理的某些应用领域，传统的将案例视为问题-解决方案空间中的点的观点是不合适的。在电子设计重用领域的具体应用的动机，我们介绍了一个广义的情况下，代表经验，自然涵盖了一个空间，而不是一个点的概念。在一个正式的框架内，我们介绍了广义情况下的语义，并推导出一个典型的相似性度量。一般情况下，可以表示在一个非常灵活的方式，通过使用约束。这种表示要求新的手段相似性评估。我们认为，原则上模糊约束满足或非线性规划可以应用于相似性计算。然而，为了避免这些方法的计算复杂性，我们提出了一个算法，一个有效的估计广义的情况下的相似性。
For certain application areas of case-based reasoning, the traditional view of cases as points in the problem-solution space is not appropriate. Motivated by a concrete application in the area of electronic design reuse, we introduce the concept of a generalized case that represents experience that naturally covers a space rather than a point. Within a formal framework we introduce the semantics of generalized cases and derive a canonical similarity measure for them. Generalized cases can be represented in a very flexible way by using constraints. This representation asks for new means of similarity assessment. We argue that in principle fuzzy constraint satisfaction or non-linear programming can be applied for similarity computation. However, to avoid the computational complexity of these approaches, we propose an algorithm for an efficient estimation of similarity for generalized cases.