Dual Bootstrap Mining with Feature Words and Contents Words
| Project/Area Number |
24500176
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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 |
Intelligent informatics
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| Research Institution | Kyushu University |
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Principal Investigator |
HIROKAWA Sachio 九州大学, 学内共同利用施設等, 教授 (40126785)
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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)
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| Project Period (FY) |
2012-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2013: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2012: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
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| Keywords | SVM / 属性選択 / ブートストラップ / 可視化 / 特徴語 / 機械学習 / テキストマイニング / support vector machine / 手がかり語 |
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| Outline of Final Research Achievements |
We developed a text mining method to extract feature words of search result using SVM (support vector machine). We succeeded to find small number of feature words that characterize the documents. We extended the bootstrap method for a measurement of generality and specificity of feature words.
We confirmed the effectiveness of the methods by applying them to analyze the real data of scientific articles, students' free comments, English writing errors, security reports, medical records and Web documents.
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Report
(4 results)
Research Products
(15 results)
