Category Classification and Effective Retrieval Based on Data Mining Technique
| Project/Area Number |
15500065
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Media informatics/Database
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| Research Institution | Ehime University (2004-2006)
Kyoto University (2003) |
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Principal Investigator |
KAWAHARA Minoru Ehime University, Center for Information Technology, Associate Professor, 総合情報メディアセンター, 助教授 (50224829)
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| Project Period (FY) |
2003 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥3,600,000 (Direct Cost: ¥3,600,000)
Fiscal Year 2006: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 2005: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 2004: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 2003: ¥1,100,000 (Direct Cost: ¥1,100,000)
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| Keywords | content delivery / category classification / data mining / Peer-to-Peer network / テキストランク / 新聞記事分類 / 文書分類 / 相関ルール / コンテンツ / 機械学習 / 再帰学習 / Webマイニング |
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| Research Abstract |
It is very difficult to categorize articles in such as newspapers. In order to categorize such articles into pre-classified categorizes effectively, we use association rules derived from the original data and then can improve the categorizing precision. On the other hand, it is also important technology to delivery content over the world and retrieve them. And we have proposed techniques to delivery and retrieve content over Peer-to-Peer network effectively with considering security.
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Report
(5 results)
Research Products
(22 results)
