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Culture under Complex Perspective: A Classification for Traditional Chinese Cultural Elements Based on NLP and Complex Networks

机译:复杂视角下的文化:基于NLP和复杂网络的传统文化元素分类

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The cultural element is the minimum unit of a cultural system. The systematic categorizing, organizing, and retrieval of the traditional Chinese cultural elements are essential prerequisites for the realization of effective extracting and rational utilization, as well as the prerequisite for exploiting the contemporary value of the traditional Chinese culture. To build an objective, integrated, and reliable classification method and a system of traditional Chinese cultural elements, this study takes the text of Taiping Imperial Encyclopedia in Northern Song Dynasty as the primary data source. The unsupervised word segmentation methods are used to detect Out-of-Vocabulary (OOV), and then the segmentation results by the THULAC tool with and without custom dictionary are compared. The TF-IDF algorithm is applied to extract the keywords of cultural elements and the Ochiia coefficient is introduced to create complex networks of traditional Chinese cultural elements. After analyzing the topological characteristics of the network, the community detection algorithm is used to identify the topics of cultural elements. Finally, a “Means-Ends” two-dimensional orthogonal classification system is established to categorize the topics. The results showed that the degree distribution in the complex network of Chinese traditional cultural elements is a scale-free network with γ ?=?2.28. The network shows a structure of community and hierarchy features. The top 12 communities have taken up to 91.77% of the scale of the networks. Those 12 topics of the traditional Chinese cultural elements are circularly distributed in the orthogonal system of cultural elements’ categorization.
机译:文化元素是文化系统的最低单位。传统的中国文化元素的系统分类,组织和检索是实现有效提取和理性利用的基本先决条件,以及利用中国传统文化当代价值的先决条件。本研究采用了一个客观,集成和可靠的分类方法和传统的中国文化元素系统,以北方宋代太平帝国百科全书为主要数据源。无监督的单词分割方法用于检测词汇流(OOV),然后比较与截图工具的分段结果,其中没有自定义字典。施用TF-IDF算法以提取文化元素的关键词,并引入了OCHIIA系数,以创建复杂的中国文化元素网络。在分析网络的拓扑特性之后,使用社区检测算法来识别文化元素的主题。最后,建立“终端”二维正交分类系统以对主题进行分类。结果表明,中国传统文化元素复杂网络中的程度分布是一种无尺寸的网络,γ=?2.28。该网络显示了社区和层次结构的结构。前12名社区占网络规模的91.77%。这些传统文化元素的12个主题是在文化元素分类的正交系统中循环分布。

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