可解释的人工智能与微调的大型语言模型用于可持续的文化遗产管理
Kai Zhou1, Wei Chen2, Wenqi Sheng3
1School of Architecture and Urban Planning, Chongqing University, Chongqing, China.
Scientific reports
|November 21, 2025
概括
这项研究开发了一个AI框架 (方面情感四倍预测) 来分析公众对遗产遗址的看法. 人工智能模型通过识别影响游客情绪的关键因素来增强遗产管理.
科学领域:
- 遗产管理 遗产管理
- 人工智能的人工智能
- 城市规划 城市规划
背景情况:
- 文化遗产遗址的重建需要了解公众的看法.
- 在历史悠久的城市地区平衡保护和现代化是复杂的.
- 作为联合国教科文组织遗址的丽江古城面临着这些挑战.
研究的目的:
- 引入一个人工智能驱动的框架,用于方面情绪四倍预测 (ASQP).
- 利用社交媒体数据评估公众对丽江古城的看法.
- 为可持续的遗产管理提供见解.
主要方法:
- 微调了使用LoRA进行情绪分析的Qwen-14B大型语言模型.
- 集成的BERT,BiLSTM,自我注意力,CNN和CRF用于增强分析.
- 分析了来自微博,大忠天平和小红洲 (2018-2024) 的社交媒体数据.
主要成果:
- 增强的Qwen-14B + ASQP模型提高了F1得分的0.97%和精度的4.48%.
- 确定了影响公众对遗产遗址看法的关键因素.
- 证明了该模型在发现隐含的情绪线索方面的有效性.
结论:
- 人工智能框架为遗产管理和城市规划提供了宝贵的见解.
- 对公众的看法分析对于平衡保护和现代化至关重要.
- 该研究支持文化遗产地区的可持续发展.
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