| Project/Area Number |
11680428
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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 |
情報システム学(含情報図書館学)
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| Research Institution | Kwansei Gakuin University |
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Principal Investigator |
OYAMA Mayumi Kwansei Gakuin University, School of Humanities, Professor, 文学部, 教授 (90103134)
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| Co-Investigator(Kenkyū-buntansha) |
OKADA Takashi Kwansei Gakuin University, Center for Information & Media Studies, Professor, 情報メディア教育センター, 教授 (00103135)
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| Project Period (FY) |
1999 – 2002
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| Project Status |
Completed (Fiscal Year 2002)
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| Budget Amount *help |
¥2,600,000 (Direct Cost: ¥2,600,000)
Fiscal Year 2002: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2001: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 2000: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 1999: ¥900,000 (Direct Cost: ¥900,000)
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| Keywords | knowledge discovery / data mining / discovery of rule / parsing tree / corpus data / graph structural data / multivariate analysis / relative indexing / 相関ルール探索法 / 時系列データ / 散布図 |
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| Research Abstract |
The outline of this research is as follows.
1. Development of data-mining tool :
(1) Improvement of data conversion software was created using the LISP language in order to indicate brief the rule drawn. This software sets up one word in a corpus, and attaches a relative index to the word connected with it. Furthermore, a semantic distance and the attribute of directivity are added to them.
(2) It experimented in the data outputted by (1) using Intelligent Miner. Furthermore, the experiment which makes network connection for Intelligent Miner on RX600 (IBM) with IBM PC710 was conducted. The work environment of an experiment has improved by this.
(3) The cascade model aiming at making flexible data mining possible on a propositional logic level was proposed. The data-mining system DISCAS which realizes this was developed.
(4) The data-mining tool using the constellation graph aiming at visual mining was developed. As for this, a display at the 2-dimensional plane of multivariate data and group-ization for data distinction were attained.
2. Application of data-mining tool : Using the corpus data of
(1) EDR English and Japanese, verbal relative node indexation was performed and correlation rule search was performed.
(2) The feature extraction of a literary work was performed and new knowledge was acquired.
(3) Application to chemistry structure data with graph structure was performed, and new knowledge was acquired by the relation between structure and the chemical characteristic.
(4) As application to mental data, new knowledge was acquired about the consciousness structure of the college student of Japan and China, and parents' bringing-up model.
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