Encyclopedia of Database Systems

Living Edition
| Editors: Ling Liu, M. Tamer Özsu

Graph Mining

  • Hong Cheng
  • Jeffrey Xu Yu
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4899-7993-3_80737-1



Graph mining is defined in general as mining non-trivial graph structures from a single graph or a collection of graphs. Frequent subgraph mining is a typical example of graph mining problems, and is defined as follows. Given a graph data set D = { G1, G2, , Gn} where Gi = (Vi, Ei) (1 ≤ i ≤ n) is a graph with a vertex set Vi and an edge set Ei, find all subgraphs whose support is no less than a user-specified minimum support threshold, where the support of a subgraph g is the number of graphs in D that g is subgraph isomorphic to.

Historical Background

Frequent subgraph mining was first studied by Inokuchi et al. [7], Kuramochi and Karypis [9], Yan and Han [15], and so on, with applications in chemical compound and protein structure analysis. After that, there has been extensive research in the literature that studies mining various forms of graph patterns, such as closed subgraph [16], maximal subgraph [6, 11], significant...

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Copyright information

© Springer Science+Business Media LLC 2016

Authors and Affiliations

  1. 1.Department of Systems Engineering and Engineering ManagementThe Chinese University of Hong KongHong KongChina
  2. 2.The Chinese University of Hong KongHong KongChina

Section editors and affiliations

  • Lei Chen
    • 1
  1. 1.Hong Kong University of Science and TechnologyHong KongChina