| Budget Amount *help |
¥2,990,000 (Direct Cost: ¥2,300,000、Indirect Cost: ¥690,000)
Fiscal Year 2017: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2016: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| 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.
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