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本工作采用了一种称之为区间统计的模糊统计方法,对三个维度上的量词或分类词作了经验的赋值工作。它们分别涉及差异量词、及完好性和肯定性的分类词。差别量词有‘无’,‘几乎无’,‘较小’,‘中’,‘较大’,‘很大’,‘极大’。完好性分类词有‘劣’,‘差’,‘可’,‘良’,‘优’。有关肯定性的有‘少许’,‘基本’,‘坚决’。文中列出了若干统计的指数。它们相应于每个词义的模糊集隶属函数,心理量表值和模糊度。从所得结果中可以表征,所有给定的语词,除极个别外,都属模糊概念。还可看到:在它们之间有着严格的序关系。在心理量表上,相邻的有序词义之间的距离是不等的,而且各自都有不同的模糊度。
This work uses a fuzzy statistical method called Interval Statistics, which empirically evaluates quantifiers or classifiers in three dimensions. They refer to difference quantifiers, respectively, and categorical terms of completeness and certainty. The difference quantifiers are None, Almost None, Little, Medium, Larger, Great, Great. Integrity classification of the word ’bad’, ’poor’, ’can’, ’good’, ’excellent’. Something about affirmations is ’a little’, ’basic’, ’hard’. The article lists a number of statistical indicators. They correspond to the fuzzy set membership function, the psychometric scale and the ambiguity for each word meaning. From the results that can be characterized, all given words, except in very few cases, are fuzzy concepts. You can also see that there is a strict order relationship between them. On the psychometric scale, the distance between adjacent ordered words is unequal, and each has a different degree of ambiguity.