An active recommendation method for Vegetable production knowledge services
Aiming at the complex and dynamic characteristics of knowledge requirements in the stages of vegetable production,such as variety selection,pest and disease control,and field management,an active recommendation method for vegetable production knowledge services is proposed to provide effective support for personalized agricultural management.Taking the construction of knowledge graph as the goal,the dynamic user interest modeling based on self-attention mechanism,hierarchical embedding technology representation,and multi-hop reasoning mechanism of graph neural network(GNN)are combined to screen and aggregate complex relationship information layer by layer to achieve accurate recommendation of vegetable production knowledge services.The experimental results show that the proposed method is significantly superior to the existing advanced models in terms of recommendation accuracy and performance indicators,and can adapt to the dynamic knowledge requirements of different stages of vegetable production.This study provided an efficient solution for personalized agricultural management and intelligent decision-making,and new ideas and methods for the research of agricultural knowledge service recommendation methods.
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