Information extraction from a large number of micro-sensory data without location attribute
| Project/Area Number |
25330099
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Information network
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| Research Institution | Chiba University |
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Principal Investigator |
Shioda Shigeo 千葉大学, 工学(系)研究科(研究院), 教授 (70334167)
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| Project Period (FY) |
2013-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2015: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2014: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2013: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | センサ / 位置推定 / グラフ描画 / オンラインソーシャルネットワーク / ランダムウォーク / 対象物カウント / ユビキタス / 対象物数推定 / レンジフリー / センシング / 検出 / ランダムウォークサンプリング / 確率測度変換 / 最適化 / 対象物 |
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| Outline of Final Research Achievements |
Fundamental theories for extracting the meaningful information from a large number of micro-sensory data collected by numerous sensors located in real or virtual world are established, and their applications to various subjects are examined. Particular focus are put on the following subjects: (1) cooperative sensor localization based on inter-sensor distances，(2) cooperative sensor localization based on binary inter-sensor-distance information, (3) graph drawing method parameterized for varying the layout, (4) target object counting using binary proximity sensors via cluster identification，(5) random-walk-based biased sampling for data collection in on-line social networks.
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Report
(4 results)
Research Products
(29 results)
