Study on Efficient Retrieval Methods for Large-scale Structured Data by Numerical Approaches
| Project/Area Number |
21500104
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Media informatics/Database
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| Research Institution | Tokyo Metropolitan University |
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Principal Investigator |
KATAYAMA Kaoru 首都大学東京, システムデザイン学部, 准教授 (00336520)
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| Project Period (FY) |
2009 – 2011
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| Project Status |
Completed (Fiscal Year 2011)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2011: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2010: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2009: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 部分グラフ / 固有値 / interlace / HOSVD / PARAFAC / hypertree decomposition / 索引 / 階層グラフ / テンソルデータ / interlace定理 / グラフ / 投影データ / 位相限定相関法 / データ分類 / ハイパーグラフ / Hypertree Decomposition |
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| Research Abstract |
We develop efficient methods for retrieving substructures of large-scale graphs, hierarchical graphs and tensor data by numerical approaches. We evaluate the proposed methods experimentally with real data and artificial data, and show the cases where they are efficient in comparison with searching methods using only combinatorial approaches.
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Report
(4 results)
Research Products
(11 results)
