A Dataset for Constructing Agricultural Knowledge Graph

This dataset utilizes web crawler technology to mine data from publicly available agricultural websites. Through automated or semi-automatic data cleaning, denoising, and other processes, unstructured data is recombined into structured data, which is ultimately stored in the form of a knowledge graph. The constructed agricultural knowledge graph includes item data for 11 agricultural categories, such as grain crops, cash crops, fruits, vegetables, etc. Specifically, it includes 461 types of grain crops, 2208 types of cash crops, 1294 types of fruits, 257 types of vegetables, 118 types of edible fungi, 1161 types of flowers and trees, 142 types of aquatic products, 113 types of pesticides, 1605 types of crop diseases and pests, 519 types of veterinary drugs, and 603 types of Chinese herbal medicines, totaling 8481 subcategories. The constructed agricultural knowledge graph can provide basic data support for the development of human-machine interactive intelligent applications such as agricultural knowledge Q&A and recommendation systems.

本数据集采用网络爬虫技术，从公开可访问的农业类网站中采集数据。通过自动化或半自动化的数据清洗、降噪等处理流程，将非结构化数据重构为结构化数据，最终以知识图谱（knowledge graph）的形式进行存储。所构建的农业知识图谱涵盖11类农业领域的实体数据，包含粮食作物、经济作物、果品、蔬菜等多个类别。具体而言，其包含461种粮食作物、2208种经济作物、1294种果品、257种蔬菜、118种食用菌、1161种花木、142种水产品、113种农药、1605种作物病虫害、519种兽药以及603种中草药，总计8481个子类别。该农业知识图谱可为农业知识问答、推荐系统等人机交互智能应用的开发提供基础数据支撑。

搜集汇总

背景与挑战

背景概述

该数据集通过爬虫技术从公开农业网站采集数据，经过清洗和去噪处理，构建了一个结构化的农业知识图谱，涵盖11个农业类别（如粮食作物、经济作物、水果等），总计8481个子类别。该知识图谱旨在为农业知识问答和推荐系统等智能应用提供基础数据支持，具有数据来源广泛、类别覆盖全面的特点。