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GraphMiner

机译:GraphMiner

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摘要

Mining frequent structural patterns from graph databases is an important research problem with broad applications. Recently, we developed an effective index structure, ADI, and efficient algorithms for mining frequent patterns from large, disk-based graph databases [5], as well as constraint-based mining techniques. The techniques have been integrated into a research prototype system--- GraphMiner. In this paper, we describe a demo of GraphMiner which showcases the technical details of the index structure and the mining algorithms including their efficient implementation, the mining performance and the comparison with some state-of-the-art methods, the constraint-based graph-pattern mining techniques and the procedure of constrained graph mining, as well as mining real data sets in novel applications.
机译:从图数据库中挖掘频繁的结构模式是一个具有广泛应用的重要研究问题。最近,我们开发了一种有效的索引结构 ADI 和有效的算法,用于从基于磁盘的大型图形数据库[5]中挖掘频繁模式,以及基于约束的挖掘技术。这些技术已集成到研究原型系统- GraphMiner 中。在本文中,我们描述了 GraphMiner 的演示,其中演示了索引结构和索引的技术细节。挖掘算法,包括高效实现,挖掘性能以及与某些最新方法的比较,基于约束的图模式挖掘技术和约束图挖掘过程以及在新颖中挖掘真实数据集应用程序。

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