Development of knowledge discovery system and research of business process for the implementation
| Project/Area Number |
15500096
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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 |
Intelligent informatics
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| Research Institution | Osaka Sangyo University |
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Principal Investigator |
HAMURO Yukinobu Osaka Sangyo University, Assistant Professor, 経営学部, 助教授 (90268235)
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| Co-Investigator(Kenkyū-buntansha) |
KATOH Naoki Kyoto University, Professor, 工学研究科, 教授 (40145826)
YADA Katsutoshi Kansai University, Assistant Professor, 商学部, 助教授 (00298811)
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| Project Period (FY) |
2003 – 2004
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| Project Status |
Completed (Fiscal Year 2004)
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| Budget Amount *help |
¥3,700,000 (Direct Cost: ¥3,700,000)
Fiscal Year 2004: ¥1,400,000 (Direct Cost: ¥1,400,000)
Fiscal Year 2003: ¥2,300,000 (Direct Cost: ¥2,300,000)
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| Keywords | data mining / knowledge discovery / MUSASHI / open source software / database / XML |
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| Research Abstract |
In our research project, we have tried to develop the KDD system that can be applied to the entire KDD process, for the purpose that the system will be used in an actual company. We have achieved the following three points.
1.Analytical methods
We had joint research projects with some companies (retail companies like supermarket and department store) on knowledge discovery. Those companies provided us with actual sales transaction data with customer ID. Using those data we developed analytical methods that provide a useful knowledge, by which the companies can implement an effective marketing action. We developed following three methods mainly.
(1)Knowledge discovery on store arrangement in a department store using genetic algorithm
(2)Knowledge discovery in brand purchasing pattern using network flow estimation
(3)Consumer Behavior Analysis by graph mining technique
2.Algorithms used in the methods
We developed efficient algorithms for the above analytical methods. We developed the following three methods mainly.
(1)Algorithms required for data preprocessing
(2)Extension of the algorithm originally used in gene analysis technology to the analysis of business data
(3)Efficient algorithms for approximating a multi-dimensional voxel terrain by a unimodal terrain
3.Developing a software
We have developed a KDD software named "MUSASHI", which was released on the web of "musashi.sourceforge.jp" on 10 July, 2003. Most of the analytical methods and the algorithms mentioned above were already implemented in MUSASHI.
More than 60,000 of people had visited on the web page and the software had been downloaded about 5,200 times since opening the web page, which shows our research result is generally accepted.
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Report
(3 results)
Research Products
(39 results)
