Journal of KIISE:Computing Practices and Letters (한국정보과학회논문지:컴퓨팅의 실제 및 레터)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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A Data Mining System for Supporting of Business Intelligence in e-Business

e-Business에서의 BI지원 데이타마이닝 시스템

  • Lee, Jun-Wook (Dept. of Computer Engineering, Chungbuk National University) ;
  • Baek, Ok-Hyun (Agency for Defense Development) ;
  • Ryu, Keun-Ho (Dept. of Electrical Elecronic Computer Engineering, Chungbuk National University)
  • 이준욱 (충북대학교 컴퓨터과학과) ;
  • 백옥현 (국방과학연구소) ;
  • 류근호 (충북대학교 전기전자및컴퓨터공학부)
  • Published : 2002.10.01
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Abstract

As the interest in business interest is increased, data mining is increasingly used in BI as the core technique. To support Business Intelligence in e-business environment, the integrated data mining system which included in various mining operations should be able to flexibly integrate with database system and also it must provide the easy and efficient interface to implement the marketing process in various business applications. In this paper, we have implemented the EC-DaMiner system to support business intelligence in e-business area. The implemented system can be integrated with the conventional database system with the standard interface. Business applications can use MQL mining query language to discover the rules and mining result is modeled in marketing database, and the EC-DaMiner system make the implementation of business marketing process more easy.

비즈니스 인텔리젼스에 대한 관심이 증대되면서 핵심 기술로써 데이타마이닝의 적용이 증대되고 있다. e-Business에서의 비즈니스 인텔리젼스를 지원하기 위해 다양한 마이닝 연산을 통합적으로 제공하는 마이닝 시스템은 데이타베이스 시스템과 유연하게 통합될 수 있어야 하며, 또한 다양한 비즈니스 응용에서의 마케팅 프로세스를 쉽게 구현할 수 있는 인터페이스를 제공하여야 한다. 이 연구에서는 e-Business영역에서의 BI를 지원하기 위해 데이타마이닝 기법을 통합적으로 제공하는 시스템으로써 EC-DaMiner 시스템을 설계, 구현하였다. 데이타마이닝 시스템은 기존의 데이타베이스 시스템과의 표준적인 인터페이스를 통하여 연동될 수 있도록 하였다. 아울러 비즈니스 어플리케이션들은 마이닝 질의어인 MQL을 통하여 규칙을 탐사하고 탐사된 규칙을 기존의 마케팅 데이타베이스에 모델화하여 반영함으로써 마케팅 전략의 구현을 용이하게 하였다.

Keywords

References

  1. Q. Chen, U. Dayal, and M. Hsu, 'OLAP-Based Data Mining for Business Intelligence Applications in Telecommunications and E-commerce,' In Proc. of the Int'l Workshop on Databases in Networked Information Systems, pp.1-19, 2000
  2. J. Mrazek, 'Data Mining for Robust Business Intelligence Solutions,' PKDD 1999
  3. W. Colin, 'The IBM Business Intelligence Software Solution,' Database Associates, 2000
  4. U. Fayyad, G. Piatetsky-Shaprio, P. Smyth, and Uthurusamy, Advanced in Knowledge Discovery and Data Mining, AAAI/MIT Press, 1996
  5. G. Piatetsky-Shaprio, J. Frawley, Knowledge discovery in databases, AAAI/MIT Press. 1991
  6. IBM Research Center, 'Developing Tightly-Coupled Applications on IBM DB2/CS Relational Database System: Methodology and Experience,' IBM Research Report RJ 10005(89094), 1995
  7. S. Sarawagi, S. Thomas, and R. Agrawal, 'Integrating Mining with Relational Database Systems: Alternatives and Implications,' In Proc. of the ACM SIGMOD Int'l Conference on Management of Data, pp343-353, 1998
  8. H. T. Kim, E-Commerce Marketing Strategy, SamGakHyung Press, 1999
  9. 이용준, 서성보, 류근호, 김혜규, '시간 간격을 고려한 시간 관계 규칙 탐사', 정보과학회논문지, 제28권 제3호, 2001
  10. R. Agrawal, et al., 'The Quest Data Mining System,' In Proc. Of the Int'l Conference on Knowledge Discovery in Databases and Data Mining, pp.244-249, 1996
  11. J. Han, et al., 'DBMiner: A System for Data Mining in Relational Databases and Data Warehouses,' In Proc. of CASCON, 1997
  12. IBM DB2 Intelligent Miner for Data, http://www-4.ibm.com/software/ data/iminer/fordata/
  13. M. King, et al., 'Evaluation of Fourteen Desktop Data Mining Tools,' IEEE International Conference on Systems, Man, and Cybernetics, 1998 https://doi.org/10.1109/ICSMC.1998.725108
  14. J. Han, et al., 'DBMiner: A System for Mining Knowledge in Large Relational Databases,' In Proc. of the Int'l Conference on Data Mining and Knowledge Discovery, pp.250-255, 1996
  15. R. Agrawal, T. Imielinski, and A. Swami, 'Mining association rules between sets of items in large databases,' In Proc. Of the ACM SIGMOD Conference on Management of Data, pp.207-216, 1993 https://doi.org/10.1145/170035.170072
  16. R. Agrawal and R. Srikant, 'Fast Algorithms for Mining Association Rules in Large Data,' In Proc. Of Int'l Conference on Very Large Databases, pp.487-499, 1994
  17. R. Sri kant, and R. Agrawal, 'Mining Generalized Association Rules,' In Proc. Of Int'l Conference on Very Large Databases, pp.407-419, 1995
  18. R. Agrawal, et al., 'Mining Sequential Patterns,' In Proc. of the Int'l Conference on Data Engineering, pp.3-14, 1995
  19. R. Srikant and R. Agrawal, 'Mining Sequential Patterns: Generalizations and Performance Improvements,' In Proc. of the Int'l Conference on Extending Database Technology,pp.3- 17, 1996
  20. R. Agrawal, K. Lin, H. Sawhney, and K. Shim, 'Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases,' In Proc. of the Int 'l Conference on Very Large Databases, pp.490-501, 1995
  21. M. Mehta, R. Agrawal, and J. Rissanen, 'SLIQ:A fast scalable classifier for data mining,' In proc. Of Int'l Conference Extending Databases Technology, 1996
  22. J. Shafer, R. Agrawal, and M. Mehta, 'SPRINT: A Scalable Parallel Classifier for Data Mining,' In Proc, of the Int'l Conference on Very Large Databases, pp.544-555, 1996
  23. R. Agrawal and G. Psaila, 'Active data mining,' In Proc. Of the Int'l conference on Knowledge Discovery in Databases and Data Mining, pp.3-8, 1995
  24. J. Han, Y. Fu, K. Koperski, W. Wang, and O. Zaiane, 'DMQL: A Data Mining Query Language for Relational Databases,' SIGMOD'96 Workshop. on Research Issues on Data Mining and Knowledge Discovery, 1996
  25. K. Keiser, J. Rushing, H. Conover, and S. Graves, 'Data Mining System Toolkit for Earth Science Data,' Earth Observation (EO) & Geo-Spatial (GEO) Web and Internet Workshop '99, 1999
  26. 이정무, Introduction to Data Mining with SQL Server 2000, Microsoft Tech-Ed 2000, 2000
  27. S. Thomas and S. Sarawagi, 'Mining Generalized Association Rules and Sequential Patterns Using SQL Queries,' In Proc, of the Int'l Conference on Knowledge Discovery in Databases and Data Mining, pp.344-348, 1998
  28. T. Imielinski, A. Virmani, and A. Abdulghani, 'DataMine: Application Programming Interface and Query Language for Database Mining,' In Proc. of the International Conference on Knowledge Discovery and Data Mining, pp.256-262, 1996
  29. M. Brohman, M. Parent, M. Pearce, and M. Wade, 'The Business Intelligence Value Chain: Data Driven Decision Support in a Data Warehouse Environment: An Exploratory,' In Proc. of the Int'l Conference on System Sciences, 2000 https://doi.org/10.1109/HICSS.2000.926905
  30. 류근호, 이준욱, 이용준, 'eCRM을 위한 시간 데이타마이닝', 한국정보과학회 데이타베이스연구회지, 제17권 제1호, 2001
  31. 류근호, 'CyberPost BI 기술 개발', 한국 전자통신 연구원 위탁과제 최종 보고서, 2000