基于数学模型分析的汉语词汇深度研究

发布时间：2019-01-29 00:52

【摘要】：本文以汉语词汇为研究对象，在分析汉语词汇的特征以及比较汉语词汇与其它语系词汇异同的基础上给出了汉语词汇深度的概念，并提出了相应的操作性定义。然后，从读音、书写形态、语义与搭配能力及使用频率等方面来讨论词汇深度的定量刻画问题。借助数学建模的基本理论和方法，对汉语词汇深度进行了比较合理的量度，建立了结构性数学模型并提出了相应的求解算法。在此基础上，对新HSK词汇表中部分行为动词做了基于深度的聚类分析，对它们进行重新分级。所得到的各级词汇的特征比较明显，易于测量和评价，为新HSK词汇更科学合理定级提供参考，同时也对教材编写、教学内容的选取都有借鉴意义。本文共分为四个部分：第一部分为引言，这部分提出了汉语词汇深度这一概念，说明了本课题研究的缘由，交代了研究背景，，综述了目前国内外研究动态，同时也阐述了本文的研究价值和意义。第二部分从读音、书写形态、语义与搭配以及使用频率四个大的方面分析了影响汉语词汇深度的主要因素，建立了汉语词汇深度刻画的结构性数学模型，并提出了求解算法。第三部分针对第二部分所提的模型和算法，利用K-均值聚类分析方法，对从新HSK词汇表中随机选取的415个行为动词做聚类分级，并对结果做相应的解读和说明。最后一部分为结语，这部分以简练的语言对全文的内容进行了概括与总结，也指出了本文研究的不足及未来的研究设想。
[Abstract]:On the basis of analyzing the characteristics of Chinese vocabulary and comparing the similarities and differences between Chinese vocabulary and other languages, this paper gives the concept of depth of Chinese vocabulary and puts forward the corresponding operational definition. Then, the quantitative description of lexical depth is discussed from the aspects of pronunciation, writing form, semantic and collocation ability and frequency of use. With the help of the basic theory and method of mathematical modeling, the depth of Chinese vocabulary is measured reasonably, the structural mathematical model is established and the corresponding algorithm is proposed. On this basis, some behavioral verbs in the new HSK vocabulary are analyzed based on depth clustering, and they are reclassified. The characteristics of all levels of vocabulary are obvious, easy to measure and evaluate, which provides a reference for the new HSK vocabulary classification, and also has reference significance for the compilation of teaching materials and the selection of teaching content. This paper is divided into four parts: the first part is the introduction, which puts forward the concept of depth of Chinese vocabulary, explains the reason of this research, explains the research background, and summarizes the current research trends at home and abroad. At the same time, it also expounds the research value and significance of this paper. The second part analyzes the main factors that affect the depth of Chinese vocabulary from the aspects of pronunciation, writing form, semantic and collocation, and frequency of use, establishes the structural mathematical model of depth characterization of Chinese vocabulary, and proposes a solution algorithm. In the third part, according to the model and algorithm proposed in the second part, we use the K-means clustering analysis method to cluster 415 behavioral verbs randomly selected from the new HSK vocabulary, and interpret and explain the results accordingly. The last part is the conclusion, which summarizes and summarizes the content of the paper in concise language, and also points out the deficiency of this study and the future research ideas.
【学位授予单位】：湖南大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：H195

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