Abstract
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.
Highlights
Traditional Chinese culture was formed by the precipitation and accumulation of psychological and behavioral characteristics in its long history [1]
Cultural elements are the basic units that constitute the cultural system. e use of traditional Chinese cultural elements has been increasingly valued by scholars who are in the field of cultural creation and management
Based on the literature review of previous studies, this paper is organized as follows: Section 2 gives a brief review of the current research on the classification of traditional Chinese cultural elements and the application of complex networks in natural language processing; Section 3 describes the data course; Section 4 proposes the construction of a complex network of traditional Chinese cultural elements; Section 5 analyzes its network topology; Section 6 focuses on the theme detection and complete classification of this network; and Section 7 concludes with contributions of this study and scope for future research
Summary
Traditional Chinese culture was formed by the precipitation and accumulation of psychological and behavioral characteristics in its long history [1]. Is research proposes a theoretical method that directly extracts a complete classification of cultural elements from traditional Chinese cultural classics textrual data sources using natural language processing techniques, complex network model with its community detection method. Based on the literature review of previous studies, this paper is organized as follows: Section 2 gives a brief review of the current research on the classification of traditional Chinese cultural elements and the application of complex networks in natural language processing; Section 3 describes the data course; Section 4 proposes the construction of a complex network of traditional Chinese cultural elements; Section 5 analyzes its network topology; Section 6 focuses on the theme detection and complete classification of this network; and Section 7 concludes with contributions of this study and scope for future research
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
