2017 Fiscal Year Final Research Report
Fast Graph Analysis using Frequent Subgraphs
| Project/Area Number |
16H06650
|
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| Research Category |
Grant-in-Aid for Research Activity Start-up
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| Allocation Type | Single-year Grants |
|---|
| Research Field |
Multimedia database
|
|---|
| Research Institution | University of Tsukuba |
|---|
Principal Investigator |
|
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| Project Period (FY) |
2016-08-26 – 2018-03-31
|
| Keywords | グラフ / データベース / アルゴリズム |
|---|
| Outline of Final Research Achievements |
The goal of this project is to develop efficient algorithms for large-scale graphs by capturing frequent subgraph structures. Specifically, in this project, we tackled to compute graphs with more than one hundred million nodes within short a few seconds. We proposed two algorithms in this project: (1) A structural graph clustering algorithm, and (2) an efficient random-walk analysis on graphs. Our experimental analysis on large-scale graphs showed that our algorithms achieved from 10 times to 100 times faster than the state-of-the-art algorithms.
|
| Free Research Field |
データベース
|
