最后是将每一层的输出求平均作为item和user的最终表示: 接下来是个性化的session encoder部分。应用一个item-level的注意力机制来combine当前会话内的item信息。 将网络更新得到的项目的表示拼接上位置编码,再经过线性映射,最后将会话内item的表示求平均来作为basic session preference。然后是常见的求会话内每个item的权重...
Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation 面向个性化会话推荐的异构全局图神经网络 发表于: 存在的问题:在现有的工作中,建模用户偏好时往往忽略了用户历史会话,导致不能实现个性化推荐。现有的基于会话的个性化推荐仅限于当前用户的会话,忽略了其他用户历史会话中有用的项目转...
①Title:个性化Session序列推荐: Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation; ②论文链接:arxiv.fenshishang.com/p 作者相关 同济大学/西蒙菲莎大学 + JD( Bo Long ) Motivation动机&Challenge&挑战: 启发:Session到Session的推荐,即预测短期交互会话的下一个交互Session?
Heterogeneous graphs (HGs) also called heterogeneous information networks (HINs) have become ubiquitous in real-world scenarios. Recently, employing graph neural networks (GNNs) to heterogeneous graphs, known as heterogeneous graph neural networks (HGNNs) which aim to learn embedding in low-dimensional...
Star859 This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL. pytorchheterogeneousgraph-neural-networksdgl UpdatedOct 31, 2024 Python BabitMF/bmf Star798 Cross-platform, customizable multimedia/video processing framework. With strong GPU acceleration, heterogeneous...
Recently, graph neural networks (GNN) have shown strength in learning low-dimensional representations of individual cells by propagating neighbor cell features and constructing cell-cell relations in a global cell graph9,10. For example, our in-house tool scGNN, a GNN model, has demonstrated superi...
While Graph Neural Networks (GNNs) have achieved remarkable results in a variety of applications, recent studies exposed important shortcomings in their ability to capture heterogeneous structures and attributes of an underlying graph. Furthermore, though many Heterogeneous GNN (HGNN) variants have been ...
论文信息 论文标题:Jointly embedding the local and global relations of heterogeneous graph for rumor detection论文作者:Chunyuan Yuan, Qianwen Ma, Wei Zhou, Jizhong
Scalable Graph Neural Networks for Heterogeneous Graphs Setup Dependencies torch==1.5.1+cu101 dgl-cu101==0.4.3.post2 ogb==1.2.1 dglke==0.1.0 Docker We have prepared a dockerfile for building a container with clean environment and all required dependencies. Please checkout instructions indocker...
《Heterogeneous Graph Neural Networks for Malicious Account Detection》解读一:Connected Subgraph 论文的标题可以翻译为《用于恶意账户检测的异构图神经网络》,根据设备聚集性(device aggregation)和行为聚集性(activity aggregation)这两个恶意账号的特征来构建图网络。