A knowledge graph (KG) is one solution to improve the recommendation system's performance. The existing solutions do not consider the side information and semantic relationship from the knowledge graph, which results in the problem of accuracy of the recommendation and the pr...
In this paper, a knowledge graph-based recommendation system was proposed enriched with knowledge graph representation learning and neural collaborative filtering. The proposed recommendation system first presents data in the form of a knowledge graph which is constructed based on the user-user, user-ta...
[KGAT]KGAT: Knowledge Graph Attention Network for Recommendation(2019,推荐系统) 1.方法概述 这篇文章提出了一种新的方法,叫做知识图谱注意力网络(KGAT),它能够显式地利用知识图谱中的高阶关联信息来提升推荐效果。它基于图神经网络(GNN)的框架,递归地从一个节点的邻居节点传播嵌入信息,同时利用注意力机制来...
一、KGAT: Knowledge Graph Attention Network for Recommendation(知识图谱注意网络推荐) [文档下载链接;https://pan.baidu.com/s/16IyKa-m5zNU48BPwDKGAcA?pwd=e913 提取码:e913 哔哩哔哩视频链接:基于知识图谱+图注意力网络的推荐模型(KGAT)_哔哩哔哩_bilibili ] 1.论文信息简介: (1)原文地址:https://doi...
3.2.1 Aggregation Layer over Intent Graph 文章先从IG中提炼collaborative information。CF是一个很有效果的方法。由此启发,将个人历史记录视为个人用户的预先存在的特征。此外,在用户intent的粒度级别捕获更细粒度的patterns,并可以假设具有相似意图的用户将对项目表示出类似的偏好。假设u是IG中的一个用户,则使用Nu=...
知识图谱词嵌入(Knowledge Graph Embedding,KGE)模型:如图6的右侧部分,将知识图谱三元组中的前2个(电影ID和关系实体)作为输入,预测出第3个(目标实体)。 图6 MKR框架 在3个子模型中,最关键的是交叉压缩单元模型。下面就先从该模型开始一步一步地实现MKR框架。
To address these challenges and enhance knowledge-graph-based recommendation methods that ignore auxiliary information and framework redundancy in neighborhood information aggregation, this study proposes a novel graph neural network recommendation model based on interactive embedding. This model capitalizes on...
a unified framework for DTI prediction by combining knowledge graph (KG) and recommendation system. This framework firstly learns a low-dimensional representation for various entities in the KG, and then integrates the multimodal information via neural factorization machine (NFM). KGE_NFM is evaluated...
To provide more accurate, diverse, and explainable recommendation, it is compulsory to go beyond modeling user-item interactions and take side information into account.为了提供更准确、多样和可解释的推荐,必须超越对用户项交互的建模,并考虑辅助信息。 笔记原本仅作为个人复习用,出现错漏和常识性问题均属正常...
Recommendation system, online health forum, graph neural networks, medical knowledge graph INTRODUCTION 社交媒体的广泛使用促进了用户生成内容的创建和共享。随着社交媒体通过提供对大量知识的访问和改善他们的决策来赋予公众权力,寻求健康信息的行为变得越来越普遍[3]。根据皮尤研究中心的健康跟踪调查1,寻求有关健康主题...