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| Storage of Semantic Knowledge Hypergraph Based on a Resource Description Framework |
| Song Xueyan, Zhang Weimin, Zhang Xiangqing |
| School of Business and Management, Jilin University, Changchun 130012 |
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Abstract To address the low storage efficiency and difficulty in storing complex semantic relationships in a resource description framework (RDF), the hypergraph theory is introduced to explore a semantic knowledge graph storage model that integrates the hypergraph theory to realize the storage of hypergraph data based on the RDF and provide a reference for other scholars to use the RDF to build knowledge hypergraphs. We construct a semantic knowledge hypergraph (SKH) model suitable for hypergraphs, analyze its storage efficiency and storage capacity of complex semantic relations by comparing it with a semantic knowledge graph (SKG), and discuss its applications in knowledge retrieval, knowledge reasoning, data conversion, and visualization. We established that the SKH model has better storage efficiency and complex semantic relationship storage capacity than the SKG. The methods of knowledge retrieval and knowledge reasoning of SKG are also applicable to SKH. The SKH model data can be transformed into SKG data considerably, and the SKH model provides a diversified and expressive visualization method. It is crucial for complex semantic storage in the field of information resource management.
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Received: 30 September 2022
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