Finding Significant Subgraphs from Big Graph data
| Project/Area Number |
16K16115
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Intelligent informatics
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| Research Institution | National Institute of Informatics (2017-2018)
Osaka University (2016) |
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Principal Investigator |
Sugiyama Mahito 国立情報学研究所, 情報学プリンシプル研究系, 准教授 (10733876)
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2017: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2016: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | グラフ / グラフマイニング / 統計的有意性 / 多重検定 / 検定可能性 / パターン / 情報幾何 / 半順序集合 / 木 / データマイニング / 知識発見 / 仮説検定 |
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| Outline of Final Research Achievements |
This research project has developed methodologies for finding statistically significant substructures from massive scale graph structured datasets. We have established an information geometric formulation that enables us to remove unnecessary candidates during the search for significant subgraphs. Moreover, we have successfully constructed a learning method that can compress detected subgraphs using probabilistic logic programming. Furthermore, to further address data analysis for subgraphs, we have implemented various graph kernels that can measure the similarity between subgraphs and published as R and Python packages.
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| Academic Significance and Societal Importance of the Research Achievements |
ソーシャルネットワークから分子構造まで，様々な対象がグラフと呼ばれる構造で表現される．多くの場合，グラフ中の特定の部分構造が，重要な役割を担っている．しかし，これまでは，統計的有意性を保証しつつそれらの重要な部分グラフを発見する手法は確立されていなかった．本研究では，この目的を達成するための手法を研究するとともに，いくつかの実用的なアルゴリズムを提案することに成功した．本研究は，情報学にとどまらず，生命科学や化学など，様々な分野へ応用可能な基盤技術となることが期待される．
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Report
(4 results)
Research Products
(23 results)
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[Book] Searching for Bacterial Pathogens in the Digital Ocean---Executive Summary2017
Author(s)
Giuliano, L., Dorman, C., Bowler, C., Sugiyama, M., Vezzulli, L., Czerucka, D., Le Roux, F., D'Auria, G., Troussellier, M., Briand, F.
Total Pages
21
Publisher
CIESM Publisher
Related Report
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