石窟寺疾病监测知识图谱中的实体关系研究

Yiran Wang
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摘要

摘要石窟寺雕凿于悬崖峭壁之上,分布广泛,是中国重要的文化遗产。然而,由于其所处环境的自然灾害风险,它面临着严重的破坏和倒塌威胁。近七成的石窟寺位于地震和水灾多发地区,导致文物受到不同程度的破坏。因此,有必要采取预防措施,减少自然灾害对石窟寺的影响。知识图谱是描述物理世界中概念及其关系的结构化语义知识库,在知识组织和内容表示方面发挥着至关重要的作用。实体关系是知识的核心,既是基础数据,也是构建知识图谱和处理非结构化文本的关键任务。在石窟寺疾病监测领域,虽然数据不断增长,但对文本数据之间关联性的研究仍然不足。本文采用 BiLSTM-CRF 方法提取实体关系,并将其与石窟寺监测知识图谱进行匹配。最后,利用 Neo4j 软件对知识图谱进行编程和展示,旨在提高石窟寺自然灾害风险管理和文化遗产保护的效率。
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Research on Entity Relationships in the Knowledge Graph of Disease Monitoring in Grotto Temples
Abstract. The grotto temple, carved into cliffs and widely distributed, is a significant cultural heritage in China. However, it faces severe damage and collapse threats due to natural disaster risks in its environment. Nearly seventy percent of grotto temples are located in regions prone to earthquakes and water hazards, leading to varying degrees of damage to cultural artifacts. Therefore, preventive measures are necessary to reduce the impact of natural disasters on grotto temples. A knowledge graph, a structured semantic knowledge base describing concepts and their relationships in the physical world, plays a crucial role in knowledge organization and content representation. Entity relationships are the core of knowledge, serving as both foundational data and a key task in constructing knowledge graphs and processing unstructured text. In the field of grotto temple disease monitoring, while data continues to grow, research on the correlation between textual data remains underexplored. This paper adopts the BiLSTM-CRF method to extract entity relationships, matching them with the grotto temple monitoring knowledge graph. Finally, the Neo4j software is utilized to program and display the knowledge graph, aiming to enhance the efficiency of natural disaster risk management and cultural heritage protection for grotto temples.
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