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基于改進CASREL的水稻施肥知識圖譜信息抽取研究
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國家重點研發(fā)計劃項目(2019YFD0900705、2017YFD0700502)


Knowledge Graph Information Extraction for Rice Fertilization Based on Improved CASREL
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    摘要:

    為實現(xiàn)水稻施肥知識圖譜自動化構(gòu)建,為后續(xù)構(gòu)建水稻施肥決策系統(tǒng)提供基礎(chǔ),定義了水稻施肥體系數(shù)據(jù)結(jié)構(gòu)并制作水稻施肥數(shù)據(jù)集,結(jié)合水稻施肥數(shù)據(jù)特點,添加單位標注器,并改進CASREL解碼加入隱藏層,提出了基于RoBERTa-wwm編碼+改進CASREL解碼的信息抽取模型,同時針對編碼與解碼環(huán)節(jié)進行試驗對比。結(jié)果表明,基于該模型的F1值達到91.86%,與對比模型相比有較為顯著的提升?;诟倪MRoBERTa-wwm-CASREL的信息抽取模型能有效提高水稻施肥信息抽取效果,為水稻施肥知識圖譜構(gòu)建以及施肥決策系統(tǒng)提供基礎(chǔ)。

    Abstract:

    In order to construct a rice fertilizer knowledge structure, based on the existing rice fertilizer unstructured data information, a rice fertilizer knowledge graph entity and relationship knowledge structure was proposed and designed, through which the existing rice fertilizer information in the network was stored in the knowledge graph as structured data;in order to extract a large amount of information to be stored in the knowledge graph, and at the same time, for the information extraction i.e., the existence of the overlapping triad problem, a rice fertilizer information extraction model based on RoBERTa-wwm coding + improved CASREL decoding was proposed, and the model was improved according to the characteristics of rice fertilizer data, and relevant experimental comparisons were conducted in coding and decoding, respectively. The results showed that the F1 value of this rice fertilizer information extraction model reached 91.86%, which was a significant improvement in extraction effect compared with the comparison model. Therefore, it can be concluded that the information extraction model based on the improved RoBERTa-wwm-CASERL can effectively improve the extraction effect of rice fertilizer information, which provided a basis for the next step of constructing rice fertilizer knowledge map and rice fertilizer decision system.

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周俊,鄭彭元,袁立存,戈為溪,梁靜.基于改進CASREL的水稻施肥知識圖譜信息抽取研究[J].農(nóng)業(yè)機械學報,2022,53(11):314-322. ZHOU Jun, ZHENG Pengyuan, YUAN Licun, GE Weixi, LIANG Jing. Knowledge Graph Information Extraction for Rice Fertilization Based on Improved CASREL[J]. Transactions of the Chinese Society for Agricultural Machinery,2022,53(11):314-322.

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  • 收稿日期:2021-12-28
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  • 在線發(fā)布日期: 2022-11-10
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