| Project/Area Number |
21650031
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Single-year Grants |
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| Research Field |
Intelligent informatics
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| Research Institution | Kyushu University |
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Principal Investigator |
IKEDA Daisuke 九州大学, 大学院・システム情報科学研究院, 准教授 (00294992)
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| Co-Investigator(Kenkyū-buntansha) |
NAKATOH Tetsuya 九州大学, 情報基盤研究開発センター, 助教 (20253502)
YAMADA Yasuhiro 島根大学, 総合理工学部, 助教 (50529609)
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| Co-Investigator(Renkei-kenkyūsha) |
BABA Kensuke 九州大学, 附属図書館, 准教授 (70380681)
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| Project Period (FY) |
2009 – 2011
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| Project Status |
Completed (Fiscal Year 2011)
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| Budget Amount *help |
¥3,270,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥270,000)
Fiscal Year 2011: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2010: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2009: ¥1,200,000 (Direct Cost: ¥1,200,000)
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| Keywords | 知識発見とデータマイニング / テキストマイニング / パターン発見 / 近似文字列照合 / 例外的パターン / フーリエ変換 / 畳み込み演算 / 遺伝子情報処理 / 時系列データ / 予兆発見 |
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| Research Abstract |
The goal of this research is to develop a framework to, given large text data, discover patterns which do not appear frequently. To achieve this goal, we review our existing researches from the following two viewpoints : Mapping of letters for pattern discovery : Using an approximate pattern matching, we have proposed a pattern discovery and evaluated by experiments. In this method, we have found that mapping from several letters into one digit plays an important role. Metric space for pattern discovery : The goal of this topic is to distinguish patterns from non用atterns. Instead of a rigid metric space, we first find usual substructures, and then we find a pattern as a combination of usual substructures. We have evaluated this method by experiments on genome sequences and Web documents.
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