Semantic Modeling of Ancient Chinese Guqin Books
Shubin Zhou, Fanshuang Meng, Yanmei Huang · KNOWLEDGE ORGANIZATION · 2025
Ancient Chinese guqin books hold significant historical and academic value within traditional musical literature, representing a key expression of ancient musical aesthetics and artistic accomplishment. However, current research faces challenges due to a lack of systematic organization and in-depth exploration, which limits the depth of their study and application. This study adopts digital humanities methodologies to explore feasible approaches for semantic modeling of ancient Chinese guqin books, aiming to achieve fine-grained organization, intelligent processing, and dynamic inheritance of these texts. This study utilizes digital humanities methodologies to organize, analyze, and revitalize ancient Chinese guqin books. The research employs a structured workflow that consists of three main steps: ontology construction, knowledge graph construction, and knowledge graph visualization and application. First, key concepts within ancient Chinese guqin books are defined through ontology, which includes the creation of class hierarchies and relational attributes. Using Protégé, this ontology is constructed and validated to ensure semantic accuracy. Next, the ontology is mapped to the Neo4j graph database to create a knowledge graph that represents multi-dimensional relationships between guqin compositions, related personas, and historical contexts. Finally, the knowledge graph is visualized and queried using Cypher to uncover hidden knowledge and facilitate deeper exploration of ancient Chinese guqin books. The semantic modeling approach proposed in this study enables the representation of the complex semantic knowledge embedded in the fragmented and diverse resources of ancient Chinese guqin books in a simplified and intuitive triplet format. This method facilitates the effective integration and clear presentation of multi-source knowledge. Additionally, intelligent querying and graph-based reasoning techniques are employed to uncover hidden knowledge associations, enabling the extraction of valuable insights and knowledge discovery. These findings not only enhance the understanding of ancient guqin texts but also provide perspective and methodological references for research in related fields of the humanities. This study introduces a novel, systematic approach for the organization and application of ancient Chinese guqin books in the digital age, advancing the preservation and modernization of historical knowledge. It also lays the theoretical foundation for constructing a knowledge resource system in the era of digital intelligence that integrates “knowledge organization, data mining, and interactive perception”, as well as a technology-driven framework that connects knowledge, intelligence, and interconnectivity. The integration of ontology and knowledge graphs offers an actionable framework for knowledge discovery and serves as a valuable reference for future digital humanities applications in the preservation of ancient texts.