农业知识图谱研究综述

Survey of Agricultural Knowledge Graph

知识图谱是大数据时代下知识工程的关键技术。利用知识图谱强大的语义理解和知识组织能力,可以解决现代化农业建设中农业知识分散无序、知识覆盖范围不足等问题针对农业领域数据复杂、专业性强等特点,给出了农业知识图谱的构建方法与框架;综述了农业知识图谱构建中本体构建、知识抽取、知识融合以及知识推理四个关键技术的国内外研究现状;系统梳理了农业知识图谱在决策支持、智能问答与推荐系统的应用;最后,介绍了几个具体的农业知识图谱实例。根据农业知识图谱的研究现状,对其未来的研究方向进行了展望。

Knowledge graphs are a key technology in the era of big data,specifically for knowledge engineering.Utilizing the powerful semantic understanding and knowledge organization capabilities of knowledge graphs,issues such as scat-tered and disordered agricultural knowledge,and insufficient coverage of knowledge in the construction of modern agri-culture can be resolved.Firstly,considering the complexity and specialty of agricultural data,the construction methods and framework of agricultural knowledge graphs are introduced.Secondly,the current domestic and international research status of the four key technologies in the construction of agricultural knowledge graphs-ontology construction,knowledge extraction,knowledge fusion,and knowledge reasoning are reviewed.Furthermore,the systematic applications of agricul-tural knowledge graphs in decision support,intelligent question-answering systems,and recommendation systems are sorted out.Lastly,several specific instances of agricultural knowledge graphs are presented.Based on the current status of research on agricultural knowledge graphs,prospects for its future research directions are offered.