Spatio-Temporal Data Mining for Real World Information Analysis
| Project/Area Number |
18K11320
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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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| Review Section |
Basic Section 60080:Database-related
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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, 教授 (80347616)
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2020: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2019: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 時空間データマイニング / ソーシャルメディア / マルチモーダル / 深層学習 / 高性能データマイニング |
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| Outline of Final Research Achievements |
In these days, people post geo-social data with time and location information on social media. These posts include things that people are witnessing and they are related to real comments in the real world. Geo-spatial data including time, location and content is called geo-spatial social data. In this study, we have developed spatio-temporal data mining techniques for geo-spatial social data. These spatio-temporal data mining techniques enable us to know what is happing, when the things are happing, where the things are happing, how things are changing. We can use geo-spatial social data as an information source by using spatio-temporal data mining techniques for geo-spatial social data.
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| Academic Significance and Societal Importance of the Research Achievements |
時空間ソーシャルデータを対象とした時空間データマイニング技術を用いることでソーシャルメディア上に投稿されている情報をリアルタイムに把握することができ，観光情報，地域振興，マーケティング，防災や危機管理の情報源として時空間ソーシャルデータを有効活用することが可能となる．また，実世界の事象を多面的に分析可能となり，ソーシャルメディアのICTへの利活用に新しいイノベーションをもたらすことができる．
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Report
(4 results)
Research Products
(26 results)
