电力信息与通信技术2024，Vol.22Issue(11)：60-66,7.DOI:10.16543/j.2095-641x.electric.power.ict.2024.11.08
基于知识图谱的用户特征-关系推荐模型在电力安全教育中的应用
The Application of Knowledge Graph-based User Feature-relation Recommendation Model in Power Safety Education
徐冲 1汪凝 1倪相生1
作者信息
- 1. 国网浙江省电力有限公司,浙江省 杭州市 310000
- 折叠
摘要
Abstract
In the context of power safety education,the long-tail distribution of the employee population leads to severe sparsity in the sampled user interaction data,having a negative impact on the performance of traditional recommendation algorithms.This paper proposes a User Feature-Relation Recommendation model based on knowledge graph.It establishes a multi-task transfer-learning neural network.By introducing the F-R unit,the model can identify crucial user feature-entity relation combinations and mine the inherent rules.By utilizing entity relationship information,it significantly improves the performance of the model.Experiments have shown that this model can effectively address the sparsity issue of user interaction data for the'long-tail'group in power safety education scenarios,significantly alleviating the cold start effect.关键词
推荐模型/多任务迁移学习/知识图谱/机器学习Key words
recommendation model/multi-task transfer learning/knowledge graph/machine learning分类
信息技术与安全科学引用本文复制引用
徐冲,汪凝,倪相生..基于知识图谱的用户特征-关系推荐模型在电力安全教育中的应用[J].电力信息与通信技术,2024,22(11):60-66,7.
