| Project/Area Number |
26280085
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Partial Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Kyoto University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
平田 耕一 九州工業大学, その他の研究科, 教授 (20274558)
伊藤 公人 北海道大学, 学内共同利用施設等, 教授 (60396314)
久保山 哲二 学習院大学, 付置研究所, 教授 (80302660)
吉仲 亮 京都大学, 情報学研究科, 助教 (80466424)
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| Co-Investigator(Renkei-kenkyūsha) |
AVIS David 京都大学, 大学院情報学研究科, 元特定教授
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| Research Collaborator |
KOBAYASHI Yasuaki 京都大学, 大学院情報学研究科, 助教
IKEDA Madori 京都大学, 大学院情報学研究科
OTAKI Keisuke 京都大学, 大学院情報学研究科
KARIYAMA Kazuaki 京都大学, 大学院情報学研究科
YAMAZAKI Tomoya 京都大学, 大学院情報学研究科
NISHIMURA Shoichi 京都大学, 大学院情報学研究科
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥15,860,000 (Direct Cost: ¥12,200,000、Indirect Cost: ¥3,660,000)
Fiscal Year 2016: ¥5,850,000 (Direct Cost: ¥4,500,000、Indirect Cost: ¥1,350,000)
Fiscal Year 2015: ¥6,370,000 (Direct Cost: ¥4,900,000、Indirect Cost: ¥1,470,000)
Fiscal Year 2014: ¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
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| Keywords | データマイニング / ２項関係 / 閉集合 / 順序関係 / 木構造 / 主成分分析 / 2項関係 / 形式概念解析 / 知識発見 / データ構造 / 整数計画法 / 行列因数分解 / 密度優先探索 |
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| Outline of Final Research Achievements |
The goal of this research is to develop methods for knowledge discovery that uses both orders for attribute values and closed sets of from mixed data. Since knowledge discovery by closed set is one kind of technique called bi-clustering of binary relational data, we obtained a method for bi-clustering for matrix factorization and search of matrices. Also we analyzed relationship between closed sets obtained by various bi-clustering method. Moreover, we developed methods for principal component analysis of the tree structure using the partial order of the substructure of tree data, the thesaurus expansion using the order relation of the vocabulary in the natural language thesaurus, and discovery methods of the similarity of the tree structure data with the integer programming.
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