计算机工程与设计2024,Vol.45Issue(12) :3812-3819.DOI:10.16208/j.issn1000-7024.2024.12.038

融合语义的图神经网络饰品设计知识推荐

Graph neural network knowledge recommendation for ornaments design fused with semantic

刘运通 孙晓莹 张展
计算机工程与设计2024,Vol.45Issue(12) :3812-3819.DOI:10.16208/j.issn1000-7024.2024.12.038

融合语义的图神经网络饰品设计知识推荐

Graph neural network knowledge recommendation for ornaments design fused with semantic

刘运通 1孙晓莹 2张展3
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作者信息

  • 1. 南阳理工学院计算机与软件学院,河南南阳 473004
  • 2. 南阳理工学院信息化建设与管理中心,河南南阳 473004
  • 3. 安阳师范学院计算机与信息工程学院,河南 安阳 455000
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摘要

为将企业结构化数据中所蕴含的专业知识高效地提供给产品设计师,提出一种基于图注意力网络的饰品设计知识推荐方法.把饰品企业的结构化数据转化为图,依据专业知识图谱融入相关语义信息,构建图注意力网络模型学习设计师的历史设计习惯,用门控循环单元神经网络提取当前设计任务的操作序列特征,依据这些信息,预测饰品设计师所需的知识并进行推荐.实验结果表明,在专业领域知识推荐方面,该方法具有更好的推荐性能.

Abstract

To efficiently provide the knowledge implicated in structured data of enterprises for product designers,a knowledge recommendation method for ornaments design based on graph attention network was proposed.The structured data of ornaments enterprises were converted into graphs and the semantic information obtained from the domain knowledge graph was fused into the graphs,and a graph attention network model was constructed to learn the historical habits of the ornaments designers,and the gated recurrent unit neural(GRU)network was used to extract the features of the designing operation sequence for the cur-rent task.According to the information,the knowledge required by the ornaments designers was predicted and the knowledge was recommended to them.Experimental results show that the method has better recommendation performance in professional domain knowledge recommendation.

关键词

图神经网络/知识推荐/知识图谱/设计任务子图/注意力机制/门控循环单元/饰品设计

Key words

graph neural network/knowledge recommendation/knowledge graph/subgraph of design task/attention mecha-nism/gated recurrent unit/ornaments design

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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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