Counting frequent patterns in large labeled graphs: a hypergraph-based approach.

Counting frequent patterns in large labeled graphs: a hypergraph-based approach.
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计算大型标记图中的频繁模式:基于超图的方法。

DOI:
10.1007/s10618-020-00686-9
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发表时间:
2020
影响因子:
4.8
通讯作者:
Tu,Yi-Cheng
Tu,Yi-Cheng
中科院分区:
计算机科学3区
文献类型:
--
作者:
Meng,Jinghan;Pitaksirianan,Napath;Tu,Yi-Cheng

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近年来,图数据库的普及迅速增长。本文重点关注单图作为表示信息的有效模型及其相关的图挖掘技术。在单图环境下的频繁模式挖掘中,存在两个主要问题:支持度量和搜索方案。在本文中,我们提出了一种用于设计支持措施的新颖框架,该框架汇集了现有的基于最小图像和基于重叠图的支持措施。我们的框架建立在出现/实例超图的概念之上。在此基础上,我们能够结合现有措施的优点,设计一系列新的支持措施:最小实例(MI)措施和最小顶点覆盖(MVC)措施。更重要的是,我们表明现有的基于最小图像的支持度量是 MI 度量的上限,它也是线性时间可计算的,并且导致计数接近模式实例的数量。我们表明,不仅大多数主要的现有支持措施和本文提出的新措施可以映射到新框架中,而且它们占据了频谱的不同位置。通过利用新框架,我们发现 MVC 可以在多项式时间内近似为常数因子(以模式节点的数量表示)。与普遍看法相反,我们证明了最先进的基于重叠图的最大独立集(MIS)测量也具有常数近似算法。我们进一步表明,使用标准线性规划和半定规划技术,可以开发 MVC 和 MIS 度量的多项式时间松弛,并且它们的计数介于 MVC 和 MIS 之间。此外,我们指出 MVC、MIS 及其松弛都限制在常数因子内。总之,所有主要的支持措施都统一在基于超图的新框架中,这有助于揭示它们的边界关系和硬度属性。
In recent years, the popularity of graph databases has grown rapidly. This paper focuses on single-graph as an effective model to represent information and its related graph mining techniques. In frequent pattern mining in a single-graph setting, there are two main problems: support measure and search scheme. In this paper, we propose a novel framework for designing support measures that brings together existing minimum-image-based and overlap-graph-based support measures. Our framework is built on the concept of occurrence/instance hypergraphs. Based on such, we are able to design a series of new support measures: minimum instance (MI) measure, and minimum vertex cover (MVC) measure, that combine the advantages of existing measures. More importantly, we show that the existing minimum-image-based support measure is an upper bound of the MI measure, which is also linear-time computable and results in counts that are close to number of instances of a pattern. We show that not only most major existing support measures and new measures proposed in this paper can be mapped into the new framework, but also they occupy different locations of the frequency spectrum. By taking advantage of the new framework, we discover that MVC can be approximated to a constant factor (in terms of number of pattern nodes) in polynomial time. In contrast to common belief, we demonstrate that the state-of-the-art overlap-graph-based maximum independent set (MIS) measure also has constant approximation algorithms. We further show that using standard linear programming and semidefinite programming techniques, polynomial-time relaxations for both MVC and MIS measures can be developed and their counts stand between MVC and MIS. In addition, we point out that MVC, MIS, and their relaxations are bounded within constant factor. In summary, all major support measures are unified in the new hypergraph-based framework which helps reveal their bounding relations and hardness properties.
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