Parallel subgraph matching on massive graphs

Bo Suo, Zhanhuai Li, Wei Pan
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Abstract

While numerous applications, such as social networks, protein-protein interaction networks, and bibliographic networks, mainly consist of graph-structured data, massive graphs, of which the scales range from million nodes to billion nodes, are common-place. Searching within these kinds of graphs is urged to be efficient. Unfortunately, since the subgraph isomorphism problem is NP-complete, querying on large graphs is still challenging.
海量图上的并行子图匹配
虽然许多应用,如社交网络、蛋白质-蛋白质交互网络和书目网络,主要由图结构数据组成,但规模从百万节点到十亿节点的大规模图是常见的。在这类图中进行搜索是为了提高效率。不幸的是,由于子图同构问题是np完全的,在大图上查询仍然是一个挑战。
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