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Fast Algorithms for Intimate-Core Group Search in Weighted Graphs

机译:加权图中的亲密核心组搜索的快速算法

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Community search that finds query-dependent communities has been studied on various kinds of graphs. As one instance of community search, intimate-core group search over a weighted graph is to find a connected fc-core containing all query nodes with the smallest group weight. However, existing state-of-the-art methods start from the maximal fc-core to refine an answer, which is practically inefficient for large networks. In this paper, we develop an efficient framework, called local exploration k-core search (LEKS), to find intimate-core groups in graphs. We propose a small-weighted spanning tree to connect query nodes, and then expand the tree level by level to a connected fc-core, which is finally refined as an intimate-core group. We also design a protection mechanism for critical nodes to avoid the collapsed fc-core. Extensive experiments on real-life networks validate the effectiveness and efficiency of our methods.
机译:已经在各种图形上研究了查找依赖于查询的社区的社区搜索。作为社区搜索的一个实例,在加权图上进行的亲密核心组搜索是找到一个包含所有具有最小组权重的查询节点的fc核心。但是,现有的最先进的方法是从最大的fc-core开始来完善答案,这对于大型网络实际上是低效的。在本文中,我们开发了一种有效的框架,称为局部探索k核搜索(LEKS),以在图形中找到亲密的核群。我们提出了一个小加权的生成树来连接查询节点,然后将树逐级扩展到连接的fc-core,最终将其精炼为亲密核心组。我们还为关键节点设计了一种保护机制,以避免崩溃的fc-core。在现实生活中进行的大量实验验证了我们方法的有效性和效率。

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