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An Automatic KANSEI Fuzzy Rule Creating System Using Thesaurus

机译:使用词库创建系统的自动KANSEI模糊规则

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In this paper, we propose an automatic Kansei fuzzy rule creating system using thesaurus. In Kansei Engineering, there are a lot of words for the expression of image. However, conventional methods cannot treat these words because it is too difficult to collect enough data of all words. The proposed system is an enhanced algorithm of the conventional method that the authors proposed. A set of fuzzy rules for only one impression word are extracted from the questionnaire responses by the conventional one. With the proposed system, sets of fuzzy rules for many words defined in the dictionary are extracted. The flow of the system consists of 3 steps: (1) calculation of the weights of thesaurus networks; (2) data collection; (3) Extraction of fuzzy rules. Using a Japanese thesaurus dictionary, the sets of fuzzy rules for 1,195 impression words are extracted while the number of registered adjectives in the thesaurus is 2,822. From experimental results, the fuzzy rules extracted by the proposed system obtained higher accuracy than that extracted by the conventional one.
机译:在本文中,我们提出了一种使用词库的自动Kansei模糊规则创建系统。在Kansei Engineering中,有很多单词表达图像。然而,传统方法不能治疗这些词,因为它太难收集了所有单词的数据。所提出的系统是作者提出的传统方法的增强算法。只有一个印象词的一组模糊规则由传统的问卷响应提取。使用所提出的系统,提取字典中定义的许多单词的模糊规则集。该系统的流量由3个步骤组成:(1)计算词库网络的权重; (2)数据收集; (3)提取模糊规则。使用日本词库词典,提取1,195印象词的模糊规则集,而词库中的注册形容词的数量是2,822。从实验结果来看,所提出的系统提取的模糊规则获得的精度高于传统常规方法的准确性。

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