Study of generation of aggregated symbolic data from large data
| Project/Area Number |
15K00059
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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 |
Statistical science
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| Research Institution | Tokushima Bunri University |
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Principal Investigator |
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| Project Period (FY) |
2015-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2018: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2016: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2015: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | シンボリックデータ解析 / 可視化 / 並列分散処理 / 大規模データ / 並列分散計算 / データ可視化 / SparkR / R / 可視化ソフトウェア / HDFS / Apache Spark / MapReduce / Apache Hadoop |
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| Outline of Final Research Achievements |
In this study, we made two things possible with the goal of generating suitable aggregated symbolic data from large-scale data. One is to create data of a size that can be processed interactively by aggregating large-scale data that can not be processed by one computer. Parallel distributed processing is performed at this time. The other one produces appropriate aggregate symbolic data about the created data. Since this differs depending on the data, it performs trial and error by visualization and interactive operation. At this time, it may return to the data creation process as needed.
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| Academic Significance and Societal Importance of the Research Achievements |
適切な集約的シンボリックデータによって，データサイズが大き過ぎるために，今までは，傾向を把握できなかったようなデータの傾向を把握できるようになる．特に，可視化によって，直感的に理解できるようになる．
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Report
(5 results)
Research Products
(19 results)
