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Distributed k-core view materialization and maintenance for graphs

机译:图的分布式k核心视图实现和维护

摘要

Large graph data in many application domains dynamically changes with vertices and edges inserted and deleted over time. The problem of identifying and maintaining densely connected regions in the graph thus becomes a challenge. Embodiments of the invention describe a method using a k-core measure as a metric of dense connectivity over large, partitioned graph data stored in multiple computing servers in a cluster. The method describes steps to identify a k-core subgraph in parallel and to maintain a k-core subgraph when a new edge is inserted or an existing edge is deleted. The embodiments thus enable practitioners to identify and monitor large scale graph data, such as exemplified by multiple topical communities in a social network, in a scalable and efficient manner.
机译:许多应用程序域中的大型图形数据会随着时间的推移随着顶点和边的插入和删除而动态变化。因此,在图形中标识和维护密集连接区域的问题成为一个挑战。本发明的实施例描述了一种方法,该方法使用k核度量作为对存储在集群中的多个计算服务器中的大的分区图数据上的密集连接性的度量。该方法描述了以下步骤:当插入新边或删除现有边时,并行标识k核子图并维护k核子图。实施例因此使得从业者能够以可缩放和有效的方式识别和监视大规模图形数据,例如由社交网络中的多个主题社区例示的。

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