针对隧道病害治理中多源异构数据和不同平台间信息孤岛的挑战，为解决该领域数据融合不充分及知识问答服务缺乏的问题，设计一种基于知识图谱的隧道病害治理知识库问答系统。该系统利用知识图谱技术和Neo4j图数据库技术进行知识库构建，并基于朴素贝叶斯模型实现用户提问解析及意图识别。通过该系统，可以高效检索并精确回答与隧道病害管理相关的查询。试验结果表明，该系统在隧道病害治理知识查询和问答方面具有较好的性能和实用性，初步满足了隧道病害治理领域交互式问答的实际需求。

Aiming at the challenges of multi-source heterogeneous data and information fragmentation across digital platforms in tunnel disease treatment, an intelligent Q&A system based on a knowledge graph is presented for the tunnel disease management knowledge base. The system utilizes knowledge graph technology and Neo4j graph database technology to achieve user question classification and intention recognition using the naive Bayesian model. The system enables efficient retrieval and precise answers to queries related to tunnel disease management. Experimental results demonstrate its strong performance, practicality, and suitability for interactive question answering in the field of tunnel disease management.