旅游景区讲解词是旅游知识交际和合作推理的重要载体。本文基于旅游景区讲解词在实际旅游信息交互场景中由于内容信息含量减弱、知识转移消退、逻辑推理降低而导致游客旅游满意度下降的问题, 通过爬取检索并收集整理宁夏回族自治区139个国家A级旅游景区的讲解词资料, 使用自然语言处理 (NLP) 技术, 形成实体 (如景点、人物、事件) 和关系 (如“位于”“属于”“发生于”) 的结构化数据, 利用w3软件机器学习算法训练逻辑推理模型, 进行实体识别、关系抽取、逻辑推理和文本生成, 形成省域尺度景区讲解词知识图谱库。依靠讲解词描述逻辑的知识表示与提取, 提出讲解词推理优化的一般框架与方法, 提高景区讲解词的内容总量、知识含量和逻辑质量, 从讲解词内容供给的规范化、智能化, 推动旅游景区总体高质量供给能力的提升。

The commentary script. of tourist attractions serves as a crucial medium for the exchange of tourism knowledge and collaborative reasoning. This paper addresses the issue of declining tourist satisfaction due to the weakening of content information, the fading of knowledge transfer, and the reduction of logical reasoning in the actual tourism information interaction scenarios of tourist attraction commentary scripts. By crawling, retrieving, and compiling the textual data of commentary scripts from 139 national Agrade tourist attractions in the Ningxia Hui Autonomous Region, and utilizing Natural Language Processing ( NLP) technology, structured data comprising entities (such as scenic spots, Fig. s, and events) and relationships ( such as “located in, ” “belongs to, ” “occurred in”) is formed. The w3 software' s machine learning algorithm is employed to train a logical reasoning model, enabling entity recognition, relationship extraction, logical reasoning, and text generation, thereby establishing a knowledge graph library of scenic area commentary scripts at the provincial scale. Relying on the knowledge representation and extraction of the descriptive logic of commentary scripts, a general framework and method for optimizing commentary script. reasoning are proposed to enhance the total content, knowledge richness, and logical quality of scenic area commentary scripts. Through the standardization and intellectualization of the content supply of commentary scripts, the overall high-quality supply capacity of tourist attractions is promoted.