文章摘要
李悦,孙坦,鲜国建,赵瑞雪,李娇,黄永文,罗婷婷.面向多源数据深度融合的农作物病虫害本体构建研究[J].数字图书馆论坛,2021,(2):2~10
面向多源数据深度融合的农作物病虫害本体构建研究
Research on Ontology Construction of Crop Diseases and Pests for Deep Fusion of Multi-source Data
投稿时间:2021-01-12  
DOI:10.3772/j.issn.1673-2286.2021.02.001
中文关键词: 领域本体;农作物病虫害;数据融合
英文关键词: Field Ontology; Crop Diseases and Pests; Data Fusion
基金项目:本研究得到国家社会科学基金项目“科技论文全景式摘要知识图谱构建与应用研究”(编号:19BTQ061)资助。
作者单位
李悦 中国农业科学院农业信息研究所 
孙坦 中国农业科学院
农业农村部农业大数据重点实验室 
鲜国建 中国农业科学院农业信息研究所
农业农村部农业大数据重点实验室 
赵瑞雪 中国农业科学院农业信息研究所
农业农村部农业大数据重点实验室 
李娇 中国农业科学院农业信息研究所 
黄永文 中国农业科学院农业信息研究所 
罗婷婷 中国农业科学院农业信息研究所 
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中文摘要:
      我国农作物病虫害种类繁多,每年因病虫害的影响导致农作物产量、农民收入的损失非常严重。由于农作物病虫害数据来源广泛,数据表示、组织方式等不尽相同,信息资源处于无序与相对混乱的状态,导致领域知识难以被有效利用。本文借鉴融合多来源、多载体的专业化高质量知识资源,尝试将农作物病虫害领域本体与通用的科技文献本体以及传统的知识组织体系进行深度融合,并对本体进行形式化表示,促进领域知识的共享与语义互操作,为构建基于多源高质量数据的领域知识图谱奠定语义基础,以期实现以科技为支撑助力农作物病虫害的科学防治,为农业新型智能化知识服务实践提供相关思路。
英文摘要:
      There are many kinds of crop diseases and pests in China, and the loss of crop yield and farmers’ income is very serious every year due to the influence of diseases and pests. However, the data of crop diseases and pests come from a wide range of sources, and the data representation and organization are different. The information resources are in a state of disorder and relative chaos, which makes it difficult for domain knowledge to be effectively utilized. For this reason, this paper integrates professional and high-quality knowledge resources from multiple sources and carriers, try to deeply integrate the domain ontology of crop diseases and pests with the general scientific and technological literature ontology and the traditional knowledge organization system, and based on formalized representation of ontology, to promote the field of knowledge sharing and semantic interoperability. This lays a semantic foundation for the construction of field knowledge graph based on multi-source and high quality data, in order to realize the scientific control of crop diseases and pests supported by science and technology, and to provide relevant ideas for the practice of new intelligent agricultural knowledge service.
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