计算机工程与设计2024,Vol.45Issue(7) :2142-2149.DOI:10.16208/j.issn1000-7024.2024.07.030

融合农村居民意图的健康知识推荐方法

Health knowledge recommendations for rural residents incorporating user intention

王馨悦 吴华瑞 陈雯柏 韩笑 朱华吉 赵春江
计算机工程与设计2024,Vol.45Issue(7) :2142-2149.DOI:10.16208/j.issn1000-7024.2024.07.030

融合农村居民意图的健康知识推荐方法

Health knowledge recommendations for rural residents incorporating user intention

王馨悦 1吴华瑞 2陈雯柏 3韩笑 2朱华吉 2赵春江2
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作者信息

  • 1. 北京信息科技大学自动化学院,北京 100192;北京市农林科学院信息技术研究中心,北京 100097
  • 2. 北京市农林科学院信息技术研究中心,北京 100097;国家农业信息化工程技术研究中心,北京 100097;农业农村部数字乡村技术重点实验室,北京 100097
  • 3. 北京信息科技大学自动化学院,北京 100192
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摘要

为提高农村居民健康认知水平,提出一种融合农村地区居民意图的健康知识推荐方法.考虑到村民对不同健康知识的偏好,建模用户层中村民与健康知识间的关系路径,捕获村民获取健康知识的潜在意图,利用图卷积与注意力机制传播聚合村民意图邻居节点信息,获得村民与健康知识的高阶邻域表示,通过双交叉聚合器将初始节点与邻域表示进行聚合,增强村民与健康知识的表示能力,实现村民健康知识精确推荐.基于农村健康知识数据集验证研究模型有效性,结果表明该模型在准确率、NDCG指标上均得到了一定程度的提高.

Abstract

To improve the health awareness of rural residents,a health knowledge recommendation method that incorporated the intentions of rural residents was proposed.Considering villagers'preferences for different relationships of health knowledge,the relations path between villagers and health knowledge was modeled as the potential intentions of villagers for acquiring health knowledge at the user level.The higher-order neighborhood representations of villagers and health knowledge were obtained using graph convolution network and attention mechanism to propagate and aggregate villagers'intentions neighborhood informa-tion.To enhance villagers and health knowledge node representation,a double-cross aggregator was selected to aggregate the en-tity and neighborhood information,to achieve accurate recommendation of villagers'health knowledge.The validity of the re-search model was verified based on the rural health knowledge data set.The results show that the precision and NDCG indexes of the proposed model are improved to a certain extent.

关键词

农村/知识推荐/注意力机制/知识图谱/嵌入传播/健康知识/神经网络

Key words

rural areas/knowledge recommendation/attention mechanisms/knowledge graph/embedding propagation/health knowledge/neural network

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基金项目

科技创新2030—"新一代人工智能"重大基金项目(2021ZD0113604)

国家重点研发计划基金项目(2019YFD1101105)

国家重点研发计划基金项目(2020YFD1100602)

出版年

2024
计算机工程与设计
中国航天科工集团二院706所

计算机工程与设计

CSTPCD北大核心
影响因子:0.617
ISSN:1000-7024
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