Spatio-Temporal Analysis for Trend Information using Large-Scale Social Images
| Project/Area Number |
26330139
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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 |
Multimedia database
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| Research Institution | Hiroshima City University |
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Principal Investigator |
Tamura Keiichi 広島市立大学, 情報科学研究科, 准教授 (80347616)
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2016: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2015: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2014: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | ソーシャル画像 / 時空間マイニング / 動向情報 / ソーシャルメディア / 並列処理 / ビッグデータ / ソーシャル画像データ / 時空間データマイニング / 動向分析 / ソーシャルデータマイニング / ビッグデータ分析 / データマイニング / 時空間クラスタリング |
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| Outline of Final Research Achievements |
In these days, people on social media dispatch information by posting messages related to daily activities with image data. Image data including text data and location information are called social image data. They have become one of the most important information source for our daily life. Therefore, new spatio-temporal mining techniques for social image data are required. In this study, basic techniques of spatio-temporal data mining for enabling us to analysis “what and when happened, where is happening, and how it changes.”regarding to daily events and topics using social image data.
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Report
(4 results)
Research Products
(47 results)
