| Project/Area Number |
15K00425
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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 |
Web informatics, Service informatics
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| Research Institution | The University of Tokushima |
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Principal Investigator |
Kita Kenji 徳島大学, 大学院社会産業理工学研究部(理工学域), 教授 (10243734)
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| Co-Investigator(Kenkyū-buntansha) |
吉田 稔 徳島大学, 大学院社会産業理工学研究部(理工学域), 講師 (40361688)
松本 和幸 徳島大学, 大学院社会産業理工学研究部(理工学域), 助教 (90509754)
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2017: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2015: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | ウェブインテリジェンス / 医療・健康情報 / 事実性解析 / ソーシャルメディア / テキストの事実性解析 / ディープラーニング / テキストからの位置推定 |
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| Outline of Final Research Achievements |
In this research, in order to comprehensively understand various medical and health information existing on the WWW, we conducted extensive research on the use of geotag information, automatic extraction of medical-related keywords, and multimodal analysis on social media information.
Regarding the use of geotag information, we mainly conducted research to associate the occurrence of infection with its location information. Regarding medical-related keyword extraction, we improved the dictionary on the symptoms of the disease, and determined whether the user was infected with the disease, and classified the infected disease name. In addition, we also conducted multimodal analysis such as image understanding of graph based on deep learning.
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