int[] capacities) { this.k = k; this.capacities = capacities; nodes = new Array...
[4] I. Stanton and G. Kliot. Streaming graph partitioning for large distributed graphs. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’12, pages 1222–1230, New York, NY, USA, 2012. ACM. [5] C. Tsourakakis, C. Gkantsidis,...
Graph PartitioningElsner, Ulrich
图1 点分割(左)和边分割(右)的示例 图分割的两个目标是负载均衡load balancing(减少存储代价)和最小化切边或点minimum cuts(减少通讯代价),同时优化这两个目标是平衡图分割(balanced graph partitioning)问题,这是一个NP难的问题[2]。通常情况下松弛为优化load balancing的同时尽可能保证minimum cuts。 给定一个...
Graph clustering is a form ofgraph miningthat is useful in a number ofpractical applications including marketing, customer segmentation, congestiondetection, facility location, and XML data integration (Lee, Hsu, Yang, &Yang,2002). The graph clustering problems are typically defined into twocategories...
点分割算法有：METIS采用层次化策略，随机初始化结点进行宽度优先遍历切分；Random Hash使用哈希函数随机分配结点；LDG考虑邻居结点放置减少边丢失；Fennel对LDG算法进行改进。边分割算法有：NE考虑邻居局部性进行切分，动态调整核心与候选集；DBH通过结点度信息切分，保持低度结点局部性；HDRF结合结点度与子图负载...
Learnable Graph Matching: Incorporating Graph Partitioning with Deep Feature Learning for Multiple Object Tracking 可学习图匹配:将图分割与深度特征学习结合用于多目标跟踪 这是一篇CVPR2021年的论文。 作者提出了一些传统问题的需要改进的地方: 传统的多目标追踪问题是基于图的优化或通过深度学习直接学习解决。
Spectral Graph Partitioning 费德勒(Fiedler)的谱图划分理论是一种用于图分割的方法。该理论基于图的特征值分解,通过分析图的特征向量来实现图的划分。 具体而言,费德勒的谱图划分理论基于图的拉普拉斯矩阵。拉普拉斯矩阵是图论中一个重要的概念,它可以将图的结构信息编码为一个对称正定矩阵。
Partitioning: MaxCompute Graph calls the custom Partitioner to partition the vertices and distributes the partitions to the related workers. By default, MaxCompute Graph partitions the vertices based on the hash values of the vertex IDs modulo the number of workers. In the preceding figure, the num...
In Graph Partitioning and Graph Clustering. [54]Fan Wenfei, Liu Muyang, Tian Chao, Xu Ruiqi, and Zhou Jingren. 2020. Incrementalization of graph partitioning algorithms. Proc. VLDB Endow. 13, 10 (2020), 1261–1274. [55]Fiduccia C. M. and Mattheyses R. M.. 1982. A linear-time ...