Tea pests and diseases are among the primary constraints in the tea industry. However, practitioners often rely on books and the internet for pests and diseases information, leading to fragmented and time-consuming searches. Constructing a question-answering system based on a knowledge graph of tea pests and diseases can address these issues. This study utilizes the deep learning model BERT-BiLSTM-CRF to automatically extract triplets, enabling the automatic construction of the knowledge graph and automated question-answering based on it. This research facilitates the rapid development of a knowledge graph in the agricultural tea sector and provides solutions for the scientific prevention and control of tea pests and diseases.

An Intelligent Q&A Module for Tea Diseases and Pests Based on Automatic Knowledge Graph Construction

Francesco Marinello
2023

Abstract

Tea pests and diseases are among the primary constraints in the tea industry. However, practitioners often rely on books and the internet for pests and diseases information, leading to fragmented and time-consuming searches. Constructing a question-answering system based on a knowledge graph of tea pests and diseases can address these issues. This study utilizes the deep learning model BERT-BiLSTM-CRF to automatically extract triplets, enabling the automatic construction of the knowledge graph and automated question-answering based on it. This research facilitates the rapid development of a knowledge graph in the agricultural tea sector and provides solutions for the scientific prevention and control of tea pests and diseases.
2023
2023 IEEE International Workshop on Metrology for Agriculture and Forestry, MetroAgriFor 2023 - Proceedings
2023 IEEE International Workshop on Metrology for Agriculture and Forestry, MetroAgriFor 2023
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3544960
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