Spatial Information Research

Korea Spatial Information Society (대한공간정보학회)
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TFP tree-based Incremental Emerging Patterns Mining for Analysis of Safe and Non-safe Power Load Lines

Safe와 Non-safe 전력 부하 라인 분석을 위한 TFP트리 기반의 점진적 출현패턴 마이닝

  • 이종범 (충북대학교 컴퓨터과학과) ;
  • 박명호 (충북대학교 컴퓨터과학과) ;
  • 류근호 (충북대학교 소프트웨어학과 및 컴정연)
  • Received : 2011.01.14
  • Accepted : 2011.04.19
  • Published : 2011.04.30
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Abstract

In this paper, for using emerging patterns to define and analyze the significant difference of safe and non-safe power load lines, and identify which line is potentially non-safe, we proposed an incremental TFP-tree algorithm for mining emerging patterns that can search efficiently within limitation of memory. Especially, the concept of pre-infrequent patterns pruning and use of two different minimum supports, made the algorithm possible to mine most emerging patterns and handle the problem of mining from incrementally increased, large size of data sets such as power consumption data.

본 논문에서는 특정 지역의 전력 소비 데이터를 이용하여 safe와 non-safe 전력 부하 라인의 차이를 분석하여 정의하고, 출현패턴을 사용하여 잠재되어 있는 non-safe라인을 식별하기 위하여 제한된 메모리에서 효율적으로 패턴을 찾을 수 있는 TFP-tree 기반의 점진적 출현패턴 마이닝 알고리즘을 제안한다. 특히, 두 개의 다른 최소 지지도 값을 사용하여 전력 소비 데이터와 같은 대용량 데이터에서의 마이닝 문제를 해결한다.

Keywords

References

  1. D. W. Cheung, C. Y. Wong, J. Han, and V. T. Ng, 1996, "Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique," International Conference on Data Engineering, pp. 106-114.
  2. F. Coenen, 2004, "The TFP Association Rule Mining Algorithm," Department of Computer Science, The University of Liverpool, UK, http://www.csc.liv.ac.uk/-frans/KDD/Software/ Apriori_TFP/aprioriTFP.html.
  3. G. Dong, and J. Li, 1999, "Efficient Mining of Emerging Patterns: Discovering Trends and Differences," ACM SIGKDD Int'l Conference Knowledge Discovery and Data Mining, pp. 43-52.
  4. G. Dong, X. Zhang, L. Wong, and J. Li, 1999, "CAEP: Classification by Aggregating Emerging Patterns," Discovery Science, pp. 737-751.
  5. J. C. Platt, 1998, "Sequential Minimal Optimization: A Fast Algorithm for Training Support Vector Machines," Technical Report MST-TR-98-14, Microsoft Research.
  6. J. Han, J. Pei, and Y. Yin, 2000, "Mining Frequent Patterns without Candidate Generation," ACM Special Interest Group on Management of Data, pp. 1-12.
  7. J. R. Quinlan, 1993, "C4.5: programs for Machine Learning," Morgan-Kaufmann publishers, San Mateo, CA.
  8. N. Friedman, D. Geiger, and M. Goldszmidt, 1997, "Bayesian network classifiers," Machine Learning, Vol.29, No.2-3, pp. 131-163. https://doi.org/10.1023/A:1007465528199
  9. Q. Dou, K. Fu, H. Zhu, P. Jiang, and Z. Shi, 2010, "Associated Clustering and Classification Method for Electric Power Load Forecasting," IFIP Advances in Information and Commu-nication Technology, Vol. 340/2010, pp. 112-121.
  10. R. Agrawal, and R. Srikant, 1994, "Fast algorithm for mining Association rules," International Conference on Very Large Data Bases, pp. 487-499.
  11. T. P. Hong, C. Y. Wang, and Y. H. Tao, 2001, "A new Incremental Data Mining Algorithm Using Pre-large Itemsets," Intelligent Data Analysis, Vol. 5, No. 2, pp. 111-129.
  12. U. Fayyad, and K. Irani, 1993, "Multi-Interval discretization of countinuous-valued attributes for classification learning," international joint conference on artificial intelligence, pp. 1022-1027.
  13. W. C. Hong, 2009, "Electric load forecasting by support vector model," Applied Mathematical Modeling, Vol. 33, pp. 2444-2454. https://doi.org/10.1016/j.apm.2008.07.010
  14. W. Li, J. Han, and J. Pei, 2001,"CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rule," International Conference on Data Mining, pp. 369-376.
  15. X. Li, Z. Deng, and S. Tang, 2006, "A Fast Algorithm for Maintenance of Association Rules in Incremental Databases," Advanced Data Mining and Applications, pp. 56-63.
  16. 박상승, 손호선, 이동규, 지은미, 김희석, 류근호, 2009, "u-City응용에서의 시간 패턴을 이용한 단기 전력 부하 예측," 한국공간정보시스템학회 논문지, 제11권 제2호, pp. 177-181.
  17. 박지웅, 홍동숙, 김동오, 한기준, 2006, "시공간 이동 패턴 추출을 위한 효율적인 알고리즘," 한국공간정보시스템학회 논문지, 제8권 제2호, pp. 39-52.