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Communication Papers of the 18th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 37

Automatic Construction of Knowledge Graph of Tea Diseases and Pests

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DOI: http://dx.doi.org/10.15439/2023F6100

Citation: Communication Papers of the 18th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 37, pages 141–146 ()

Full text

Abstract. Tea production involves several stages, including planting, management, and processing, where pests and diseases can negatively impact the quality of tea and reduce the harvest, limiting the industry's development. However, the current knowledge graph for tea pests and diseases is mainly constructed in a semi-automated and manual way, resulting in low efficiency and falling short of production needs. This research constructs a domain text dataset based on the ME+R+BIESO annotation method, employs the BERT-BiLSTM-CRF model for joint extraction of entities and relationships in a triplet, and automates knowledge graph construction, saving it in the Neo4j database. The study shows that this model has improved accuracy and performance compared to previous methods and provides effective support for scientific management and production services of tea pests and diseases. The findings offer a reference for quickly constructing knowledge graphs in the crop domain.

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