基于大型语言模型自动构建的肉养殖知识图数据集
Nan Ma1,2, Fantao Kong3,4, Jifang Liu2,4
1College of Computer and Information Engineering, Xinjiang Agricultural University, Urumqi 830052, China.
Data in brief
|October 1, 2025
概括
这项研究使用大型语言模型开发了一个全面的肉养殖知识图. 该系统整合了各种数据,以改善决策和优化智能农业的生产效率.
科学领域:
- 农业科学 农业科学
- 人工智能的人工智能
- 数据科学数据科学数据科学
背景情况:
- 智能农业对于现代农业至关重要,肉养殖需要复杂的管理.
- 现有的知识图缺乏深度来捕捉肉养殖的相互依赖性,限制了决策支持.
- 需要一个全面的知识系统来优化肉生产效率.
研究的目的:
- 使用大型语言建模构建高质量的肉养殖知识图.
- 整合一个涵盖品种,环境,养和疾病预防的中国语库.
- 加强决策和优化管理在肉养殖.
主要方法:
- 利用文本扫描和网络爬虫来从农业文献和在线来源获取数据.
- 采用DeepKE框架和大型语言模型 (LLM) 来提取和完善知识.
- 在Neo4j图形数据库中存储结构化知识,以进行高效的查询和分析.
主要成果:
- 开发了一个全面的知识图数据集,涵盖肉养殖的四个核心维度.
- 成功集成多种数据源,通过验证确保准确性和一致性.
- 启用数据驱动推断和视觉管理,以优化农业战略.
结论:
- 构建的知识图为肉养殖提供了多维的见解.
- 该系统支持视觉管理,数据驱动推断和农业战略优化.
- 这种方法为提高 brojler养殖生产效率提供了新的方法.
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