Closed Frequent Subgraph Mining by Graph Closure Operation and Its Parallelization

图闭合操作的闭合频繁子图挖掘及其并行化

• 批准号: 21700167
• 负责人: OHARA Kouzou
• 金额: $ 2.75万
• 依托单位: Aoyama Gakuin University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Young Scientists (B)
• 财政年份: 2009
• 资助国家: 日本
• 起止时间: 2009 至 2010
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-21700167/
• 关键词: グラフマイニング; データマイニング; 機械学習; パターン発見; クラフマイニング

In this work, we proposed the graph closure operator, as well as an efficient method for graph isomorphism checking that takes advantage of occurrences of a graph pattern. Given a subgraph, the operator generates a closed subgraph including it, where the closed subgraph is the maximum subgraph among those which have the same frequency as the given one. Then, we developed an efficient method for enumerating all possible closed frequent subgraphs in a graph database by means of them, and parallelized its inner processes to improve its scalability.

在这项工作中，我们提出了图闭包算子，以及一种利用图模式的出现来进行图同构检查的有效方法。给定子图，算子生成包括它的闭子图，其中闭子图是与给定子图具有相同频率的子图中的最大子图。在此基础上，我们提出了一种有效的方法来枚举图库中所有可能的闭频繁子图，并对其内部过程进行了并行化以提高其可扩展性。

项目成果

Behavioral Analyses of Information Diffusion Models by Observed Data of Social Network

• DOI: 10.1007/978-3-642-12079-4_20
• 发表时间: 2010-03
• 作者: Kazumi Saito;M. Kimura;K. Ohara;H. Motoda

Selecting Information Diffusion Models over Social Networks for Behavioral Analysis

• DOI: 10.1007/978-3-642-15939-8_12
• 发表时间: 2010-09
• 作者: Kazumi Saito;M. Kimura;K. Ohara;H. Motoda