论文:Dual Channel Hypergraph Collaborative Filtering 下载地址:https://dl.acm.org/doi/pdf/10.1145/3394486.3403253...针对以上两个问题,论文提出了双通道超图卷积网络协同过滤的框架DHCF(Dual Channel Hypergraph Collaborative Filtering): 1....方法介绍 2.1 基本定义 Hypergraph主要特点是一条边可以连接任意数量的顶点,即一个点集。...超图(HyperGraph)自然具有建模高阶连接的能力。此外,超图卷积可以处理高阶相关结构,作为一种有效而深入的操作。...总结数学表达式如下 2.4 模型定义 本文使用的一个关键结构 Jump Hypergraph Convolution,在最初的超图卷积的基础上添加一个skip connect的连接,起到类似于ResNet
作者 | 乔剑博 编辑 | 李仲深 论文题目 Hypergraph Structure Learning for Hypergraph Neural Networks 论文摘要 超图是对实体之间的高阶关系进行编码的自然且富有表现力的建模工具
因此作者提出的解决方案会很有意思,利用Hypergraph超图来解决这一问题。 超图作为一种特殊的Graph,它可以连接两个以上的节点,通过该模型可以缓解各模态下用户与项之间的稀疏性问题。...如上图的示意图,展示了modality-originated hypergraph的构建,即用户1和用户2都与多个短视频进行过交互如1和2,因此在每个模态的超边上都可以连接多个item节点,如帧、声学、...超图生成模块(Hypergraph Generation Modules)。这里分为 Interest-based User和 Item两种构建方式,如上图的下半部分。...超图卷积(Hypergraph Convolution Network (HGCN))。构完超图之后,学习表示就套公式就好: 预测模块。...总结来说HyperCTR关键词是多模态+时序+组,通过基于兴趣的用户超图和项超图这两个Hypergraph来丰富每个用户和项的表示。
Filtering Geometric Disentangled Collaborative Filtering 【几何解耦的协同过滤】 Self-Augmented Recommendation with Hypergraph...And User Historical Behavior for Sequential Recommendation 【short paper,融合时间和用户历史行为的预训练模型】 Enhancing Hypergraph...Graph Network for Session-based Recommendation 【特征驱动的反射图网络】 Co-clustering Interactions via Attentive Hypergraph...Convolutional Network for Multiple Social Recommendations 【short paper,双同质超图卷积网络】 Enhancing Hypergraph...Knowledge Graph Contrastive Learning for Recommendation 【知识图谱上的对比学习】 Self-Augmented Recommendation with Hypergraph
作者 | 王汝恒 编辑 | 李仲深 论文题目 Heterogeneous Hypergraph Embedding for Graph Classification 论文摘要 最近,图神经网络因其在成对关系学习中的突出表现而被广泛用于网络嵌入
先来看看上图中和vertex有关的第①个类: HyperGraph::Vertex,在g2o的GitHub上(https://github.com/RainerKuemmerle/g2o),它在这个路径...g2o/core/hyper_graph.h 这个 HyperGraph::Vertex 是个abstract vertex,必须通过派生来使用。...然后我们看g2o 类结构图中第②个类,我们看到HyperGraph::Vertex 是通过类OptimizableGraph 来继承的, 而OptimizableGraph的定义在 g2o/core/optimizable_graph.h...我们找到vertex定义,发现果然,OptimizableGraph 继承自 HyperGraph,如下图所示 ?
Multi-grained Hypergraph Interest Modeling for Conversational Recommendation 9....Multi-grained Hypergraph Interest Modeling for Conversational Recommendation Chenzhan Shang, Yupeng...In this paper, we propose a novel multi-grained hypergraph interest modeling approach to capture user...and form a session-based hypergraph, which captures coarse-grained, session-level relations....We further conduct multi-grained hypergraph convolution on the two kinds of hypergraphs, and utilize
. // 采用超图算法生成执行计划,注意超图算法通过set optimizer_switch="hypergraph_optimizer=on"方式启用 if (thd->lex->using_hypergraph_optimizer
简读分享 | 乔剑博 编辑 | 王宇哲 论文题目 Multi-way relation-enhanced hypergraph representation learning for anti-cancer
Attentive Graph Neural Networks for Holistic Sequential Recommendation 5.Self-Supervised Multi-Channel Hypergraph...Self-Supervised Multi-Channel Hypergraph ConvolutionalNetwork for Social Recommendation ?
Towards Hierarchical Policy Learning for Conversational Recommendation with Hypergraph-based Reinforcement...Specifically, we develop a dynamic hypergraph to model user preferences and introduce an intrinsic motivation...Basket Representation Learning by Hypergraph Convolution on Repeated Items for Next-basket Recommendation...(in a basket) as a hyperedge, where the correlations among different items can be well exploited by hypergraph
刘元盛老师团队在Briefings in Bioinformatics上发表文章Prediction of multi-relational drug–gene interaction via Dynamic hyperGraph...作者提出了一种新的动态超图对比学习(Dynamic hyperGraph Contrastive Learning,DGCL)框架,利用药物和基因之间的局部和全局关系进行药物-基因相互作用预测。...Prediction of multi-relational drug–gene interaction via Dynamic hyperGraph Contrastive Learning.
Counteracting User Attention Bias in Music Streaming Recommendation via Reward Modification [18] Multi-Behavior Hypergraph-Enhanced...Transformer for Next-Item Recommendation [19] Self-Augmented Hypergraph Transformer for Recommender...In this paper, we propose a hypergraph neural network based model named HIRS....); Quanyu Dai (Huawei Noah's Ark Lab); Ji-Rong Wen (Renmin University of China) [18] Multi-Behavior Hypergraph-Enhanced...Singapore); Yanwei Yu (Ocean University of China); Chenliang Li (Wuhan University) [19] Self-Augmented Hypergraph
2023年11月13日,厦门大学刘向荣教授团队,联合湖南大学曾湘祥教授、山东大学魏乐义教授,在PLoS Computational Biology上发表文章A general hypergraph learning...作者提出了一种在生物医学网络中进行药物多任务预测的通用超图学习算法(A general HyperGraph learning algorithm for Drug multi-task predictions...A general hypergraph learning algorithm for drug multi-task predictions in micro-to-macro biomedical
文章信息: Title: You are AllSet: A Multiset Learning Framework for Hypergraph Neural Networks....可以注意到此处每个"边"可能包含了 「超过两个点」,这也就是所谓的超边(hyperedge),而这种广义的图则被称作超图(hypergraph)。
师兄:对的,SparseOptimizer是整个图的核心,我们注意右上角的 is-a 实心箭头,这个SparseOptimizer它是一个Optimizable Graph,从而也是一个超图(HyperGraph...注意看 has-many 箭头,你看这个超图包含了许多顶点(HyperGraph::Vertex)和边(HyperGraph::Edge)。...初始化 SparseOptimizer::initializeOptimization(HyperGraph::EdgeSet& eset) 设置迭代次数,然后就开始执行图优化了。
Dynamic Hypergraph Neural Networks. IJCAI 2019....Hypergraph Hypergraph Neural Networks. AAAI 2019....Hypergraph Label Propagation Network. AAAI 2020....Hypergraph Convolutional Recurrent Neural Network. KDD 2020. Jaehyuk Yi, Jinkyoo Park. 5.
Recommender Systems 论文链接: https://arxiv.org/abs/2206.13764 代码链接: https://github.com/ruizhang-ai/HIRS_Hypergraph_Infomax_Recommender_System...[4] Multi-Behavior Hypergraph-Enhanced Transformer for Next-Item Recommendation 论文链接: https://arxiv.org...为了应对这一挑战,我们设计了一个多行为超图增强型 Transformer 框架 (MBHT,Multi-Behavior Hypergraph-enhanced Transformer framework...[5] Self-Augmented Hypergraph Transformer for Recommender Systems 论文链接: https://arxiv.org/abs/2207.14338...鉴于上述挑战,这项工作提出了一种自监督超图Transformer框架(SHT,Self-Supervised Hypergraph Transformer framework),以增强基于图的协同过滤范式的鲁棒性和泛化性能
领取专属 10元无门槛券
手把手带您无忧上云