农机化研究2024，Vol.46Issue(3)：8-13,6.
基于知识图谱的番茄种植管理可视化查询
Visual Query of Tomato Irrigation Based on Knowledge Graph
摘要
Abstract
In order to improve the speed and accuracy of agricultural workers'acquisition of tomato planting management knowledge,this study described tomato planting management in different environments by graph form.A visual query sys-tem for tomato planting management was constructed based on knowledge graph.This method solved the slowness and ac-curacy problems of Neo4j by using the top-down and bottom-up modular CREATE,and built a visual query interface by using PyQt framework,and outputed the most appropriate tomato planting management knowledge through problem pre-processing and semantic similarity calculation.The experimental results show that the average response time and average accuracy of this method are 88.33%and 1.97%higher than that of Cypher query language,respectively.The operability of this method is more friendly than that of Cypher query language.This study can provide high quality planting manage-ment suggestions for tomato production and management in different environments.关键词
知识图谱/Neo4j/相似度计算/问题预处理/可视化查询Key words
knowledge graph/Neo4j/similarity calculation/problem preprocessing/visual query分类
农业科技引用本文复制引用
张宇,于合龙,郭文忠,林森,文朝武,龙洁花..基于知识图谱的番茄种植管理可视化查询[J].农机化研究,2024,46(3):8-13,6.基金项目
北京市科技计划项目(Z211100004621006) （Z211100004621006）
北京市农林科学院青年基金项目(QNJJ202027) （QNJJ202027）
宁夏回族自治区重点研发计划项目(2018BBF02024) （2018BBF02024）
