1 DANE的表现不如预期,因为它最初是为属性网络(attributed networks)设计的。 2 DynGEM和DynamicTriad的表现都优于node2vec.这三种方法都是嵌入算法——node2vec用于静态网络,而DynGEM和DynamicTriad用于捕获动态。这些结果表明了图形中动态信息的重要性。 3 所提出的动态图神经网络模型优于现有的两个有代表性的GNN,...
4 Streaming Graph Neural Networks link:https://dl.acm.org/doi/10.1145/3397271.3401092 Abstract 本文提出了一种新的动态图神经网络模型DGNN,它可以随着图的演化对动态信息进行建模。特别是,该框架可以通过捕获: 1、边的序列信息, 2、边之间的时间间隔, 3、信息传播耦合性 来不断更新节点信息。 Conclusion 在...
It is difficult to generate fake samples on graphs (i.e., node neighborhood), which obey the true historical distribution of graph data. Generative models encounter great difficulties on graphs due to the discreteness and relevance of graph data. Existing graph generative methods do not consider t...
2、Intro 3、SGNN-GR 动机 贡献 相关工作 基础 方法
Efficient streaming subgraph isomorphism with graph neural networksdoi:10.14778/3446095.3446097DuongChi ThangHoangTrung DungYinHongzhiWeidlichMatthiasNguyenQuoc Viet HungAbererKarlVLDB EndowmentPUB4722Very Large Data Bases
To tackle this problem, we propose a Streaming Traffic Flow Forecasting Framework, TrafficStream, based on Graph Neural Networks (GNNs) and Continual Learning (CL), achieving accurate predictions and high efficiency. Firstly, we design a traffic pattern fusion method, cleverly integrating the new ...
Streaming Graph Partitioning for Large Distributed Graphs Isabelle Stanton University of California Berkeley Berkeley, CA isabelle@eecs.berkeley.edu Gabriel Kliot Microsoft Research Redmond, WA gkliot@microsoft.com ABSTRACT Extracting knowledge by performing computations on graphs is becoming increasingly ...
Deep Reinforcement Learning Based on Graph Neural Network for Flexible Job Shop Scheduling Problem with Lot Streaming The flexible job shop scheduling problem with lot streaming (FJSPLS) has gained considerable attention due to its potential to significantly reduce manufac... J He,J Li - Internationa...
Jiang, W., Luo, J.: Graph neural network for traffic forecasting: a survey. Expert Syst. Appl. 207, 117921 (2022) Article Google Scholar Johnson, M.R., Woodcock, J.: The impacts of live streaming and twitch. TV on the video game industry. Media Cult. Soc. 41(5), 670–688 (20...
Streaming data refer to an unbounded sequence of real-time data points with high velocity, volume, and skewed distribution [35]. In a normal distribution, the data points on both sides of the graph are equal, whereas in a skewed distribution, the data points are not equally distributed. In...