| 研究課題/領域番号 |
21K12034
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| 研究機関 | 会津大学 |
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研究代表者 |
Rage Uday・Kiran 会津大学, コンピュータ理工学部, 准教授 (20874324)
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| 研究分担者 |
是津 耕司 国立研究開発法人情報通信研究機構, ユニバーサルコミュニケーション研究所統合ビッグデータ研究センター, 研究センター長 (40415857)
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| 研究期間 (年度) |
2021-04-01 – 2025-03-31
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| キーワード | Big data |
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| 研究実績の概要 |
This year, we have first developed an ER-model to store the air pollution data. Next, we have developed a theoritical database model by applying normal forms. Later, we have populated our theoritical model using postGres database. The air pollution data used for populating our model has been taken from the Atmospheric Environmental Regional Observation System (http://soramame.taiki.go.jp/). Next, proposed a mathetical model for representing the air pollution data as a geo-referenced time series database. The work is going to appear in IEEE FUZZ 2022.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
1: 当初の計画以上に進展している
理由
The reason is progressing smoothly. We were able to collect the data from the real-world.
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| 今後の研究の推進方策 |
The space of items in a database gives raise to an itemset lattice. This lattice represents the search space for finding interesting patterns within the data. Thus, the size of the search space is (2 power n)-1, where n represents the total number of items in a database. In this research, we plan to explore novel pruning techniques to effectively reduce the search space. In particular, we plan to investigate upper bound measures to reduce the search space.
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| 次年度使用額が生じた理由 |
We have transferred the balance to the Co-PI of this project, Koji Zettsu
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