AgriKG: An Agricultural Knowledge Graph and Its Applications

被引:37
|
作者
Chen, Yuanzhe [1 ]
Kuang, Jun [1 ]
Cheng, Dawei [3 ,4 ]
Zheng, Jianbin [1 ]
Gao, Ming [1 ,2 ]
Zhou, Aoying [1 ]
机构
[1] East China Normal Univ, Sch Data Sci & Engn, Shanghai, Peoples R China
[2] Key Lab Adv Theory & Applicat Stat & Data Sci MOE, Shanghai, Peoples R China
[3] Shanghai Jiao Tong Univ, Shanghai, Peoples R China
[4] Keydriver Inc, Shanghai, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
D O I
10.1007/978-3-030-18590-9_81
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Recently, with the development of information and intelligent technology, agricultural production and management have been significantly boosted. But it still faces considerable challenges on how to effectively integrate large amounts of fragmented information for downstream applications. To this end, in this paper, we propose an agricultural knowledge graph, namely AgriKG, to automatically integrate the massive agricultural data from internet. By applying the NLP and deep learning techniques, AgriKG can automatically recognize agricultural entities from unstructured text, and link them to form a knowledge graph. Moreover, we illustrate typical scenarios of our AgriKG and validate it by real-world applications, such as agricultural entity retrieval, and agricultural question answering, etc.
引用
收藏
页码:533 / 537
页数:5
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