中国农业机械化科学研究院集团有限公司 主管

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赵赛,杨婉霞,王巧珍,等.基于马铃薯病虫害知识图谱的问答系统[J].农业工程,2023,13(8):29-37. DOI: 10.19998/j.cnki.2095-1795.2023.08.006
引用本文: 赵赛,杨婉霞,王巧珍,等.基于马铃薯病虫害知识图谱的问答系统[J].农业工程,2023,13(8):29-37. DOI: 10.19998/j.cnki.2095-1795.2023.08.006
ZHAO Sai,YANG Wanxia,WANG Qiaozhen,et al.Question answering system based on potato pests and diseases knowledge map[J].Agricultural Engineering,2023,13(8):29-37. DOI: 10.19998/j.cnki.2095-1795.2023.08.006
Citation: ZHAO Sai,YANG Wanxia,WANG Qiaozhen,et al.Question answering system based on potato pests and diseases knowledge map[J].Agricultural Engineering,2023,13(8):29-37. DOI: 10.19998/j.cnki.2095-1795.2023.08.006

基于马铃薯病虫害知识图谱的问答系统

Question Answering System Based on Potato Pests and Diseases Knowledge Map

  • 摘要: 开展农业知识图谱的问答系统研究在整个智能农业领域中具有重要的意义。以马铃薯病虫害为例,设计了马铃薯病虫害知识图谱问答系统,通过BIO、BMES和BIOES 3种方式标注数据后设计了BIiLSTM-CRF、Word2vec-BILSTM-CRF和Bert-BILSTM-CRF 3种模型进行命名实体识别。试验结果表明,BEMS标注方式效果最佳,Bert-BILSTM-CRF模型在命名实体识别时性能最佳,其F1值为85.62%。结合Neo4j图数据库匹配相应Cypher语句实现问答交互,应用基于Javascript语言的VUE前端框架,搭建完整的问答系统页面。

     

    Abstract: Research on question answering system of agricultural knowledge map is of great significance in the field of intelligent agriculture.A question answering system of potato pests and diseases knowledge map was designed, taking potato pests and diseases as an example.After labeling data by three models of BIO, BMES and BIOES, Bilstm-CRF, Word2vec Bilstm-CRF and Bert Bilstm-CRF, were designed for named entity recognition.Experimental results showed that BEMS annotation method was the best, Bert BiLSTM CRF model has the best performance in named entity recognition, and its F1 value was 85.62%.Question and answer interaction was realized by matching corresponding cypher statements with the Neo4j diagram database, and the VUE front-end framework based on javascript language was applied to build a complete question and answer system page.

     

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