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A rough set approach to multiple dataset analysis
https://iwate-u.repo.nii.ac.jp/records/10065
https://iwate-u.repo.nii.ac.jp/records/1006523b09205-0ab0-443f-be73-e9699a7addad
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
asc-v11n2p2538-2547.pdf (472.8 kB)
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| Item type | 学術雑誌論文 / Journal Article(1) | |||||||
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| 公開日 | 2011-02-14 | |||||||
| タイトル | ||||||||
| タイトル | A rough set approach to multiple dataset analysis | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | Rough set theory | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | Fuzzy theory | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | Multiple datasets | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | Causality | |||||||
| 資源タイプ | ||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||
| 資源タイプ | journal article | |||||||
| 著者 |
Kaneiwa, Ken
× Kaneiwa, Ken
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| 著者(機関) | ||||||||
| 値 | Department of Electrical Engineering and Computer Science, Iwate University | |||||||
| 登録日 | ||||||||
| 日付 | 2011-02-14 | |||||||
| 書誌情報 |
Applied Soft Computing 巻 11, 号 2, p. 2538-2547, 発行日 2011-03-01 |
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| ISSN | ||||||||
| 収録物識別子タイプ | ISSN | |||||||
| 収録物識別子 | 1568-4946 | |||||||
| Abstract | ||||||||
| 内容記述タイプ | Other | |||||||
| 内容記述 | In the area of data mining, the discovery of valuable changes and connections (e.g., causality) from multiple data sets has been recognized as an important issue. This issue essentially differs from finding statistical associations in a single data set because it is complicated by the different data behaviors and relationships across multiple data sets. Using rough set theory, this paper proposes a change and connection mining algorithm for discovering a time delay between the quantitative changes in the data of two temporal information systems and for generating the association rules of changes from their connected decision table. We establish evaluation criteria for the connectedness of two temporal information systems with varying time delays by calculating weight-based accuracy and coverage of the association rules of changes, adjusted by a fuzzy membership function. | |||||||
| 出版者 | ||||||||
| 出版者 | Elsevier B.V. | |||||||
| 権利 | ||||||||
| 権利情報 | © 2010 Elsevier B.V. | |||||||
| DOI | ||||||||
| 関連タイプ | isIdenticalTo | |||||||
| 識別子タイプ | DOI | |||||||
| 関連識別子 | 10.1016/j.asoc.2010.08.021 | |||||||
| 著者版フラグ | ||||||||
| 出版タイプ | VoR | |||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||
