Conceptual fuzzy sets as a meaning representation and their inductive construction
Conceptual fuzzy sets as a meaning representation and their inductive construction
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作为意义表示的概念模糊集及其归纳构造
DOI：
10.1002/int.4550101102
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发表时间：
1995
影响因子：
7
通讯作者：
Toru Yamaguchi
中科院分区：
文献类型：
--
作者：
T. Takagi;A. Imura;H. Ushida;Toru Yamaguchi
模糊集提供了一个强大的符号表示真实的世界的概念，本质上是模糊的。然而，它们有问题所造成的限制的数值隶属函数，限制的逻辑表达式，缺乏上下文依赖性，等等，这些问题涉及到一个概念的意义的表示。本文提出了概念模糊集（CFS），这是一种新的模糊集类型，它与维特根斯坦（Wittgenstein）关于概念意义的思想（Philosophical Investigations，Basil Blackwell，Oxford，1953）相一致。CFS被实现为联想记忆，结合了长期记忆和短期记忆，从而降低了知识表示的复杂性。除了解决上述问题之外，CFS还提供了简单的知识表示公式和使用这些知识的过程。介绍了一种基于神经网络学习的CFS构造方法。CFS和学习方法的有效性通过它们在面部表情识别中的应用来说明。John Wiley & Sons，Inc.
Fuzzy sets provide a strong notation for representing real world concepts which are essentially vague. However they have problems caused by the restriction of numerical membership functions, restriction of logical expression, lack of context dependency, etc. These problems relate to the representation of the meaning of a concept. In this article, we propose Conceptual Fuzzy Sets (CFS), a new type of fuzzy sets which conform to Wittgenstein's ideas (Philosophical Investigations, Basil Blackwell, Oxford, 1953) on concept meaning. A CFS is realized as an associative memory, combining a long‐term memory and a short‐term memory thus reducing the complexity of knowledge representation. In addition to solving the above problems CFS provide simple formula for knowledge representation and the procedure to use this knowledge. We introduce an inductive method for constructing CFS based on neural network learning. the effectiveness of CFS and of the learning method is illustrated through their application to the recognition of facial expressions. © 1995 John Wiley & Sons, Inc.