Browse > Article
http://dx.doi.org/10.3745/KIPSTB.2003.10B.3.265

An Improved Rectangular Decomposition Algorithm for Data Mining  

Song, Ji-Young (고려대학교 대학원 전산학과)
Im, Young-Hee (대전대학교 컴퓨터정보통신공학부)
Park, Dai-Hee (고려대학교 컴퓨터정보학과)
Publication Information
The KIPS Transactions:PartB / v.10B, no.3, 2003 , pp. 265-272 More about this Journal
Abstract
In this paper, we propose a novel improved algorithm for the rectangular decomposition technique for the purpose of performing data mining from large scaled database in a dynamic environment. The proposed algorithm performs the rectangular decompositions by transforming a binary matrix to bipartite graph and finding bicliques from the transformed bipartite graph. To demonstrate its effectiveness, we compare the proposed one which is based on the newly derived mathematical properties with those of other methods with respect to the classification rate, the number of rules, and complexity analysis.
Keywords
Rectangular Decomposition; Incremental Updating; Data Mining;
Citations & Related Records
연도 인용수 순위
  • Reference
1 M.-S. Chen, J. Han and P. Yu, 'Data Mining : An Overview from Database Perspective,' IEEE Transaction on Knowledge and Data Engineering, Vol.8, No.6, pp.866-883, 1996   DOI   ScienceOn
2 J. G. Ganascia, Charade, 'Apprentissage de bases de connaissances,' Induction Symbolique et Numerique a Partir de Donnees(Cepadues-edition), pp.309-326, 1991
3 P. P. Wang, 'Advances in Fuzzy Theory and Technology,' Duke University Edition, 1994
4 M. Maddouri, A. Jaoua, 'Incremental Learning : Proposition and evaluation of methods,' Proceedings of the Joint International Conference on Information Science JICIS '95, 1995
5 V. Novak, 'Fuzzy Sets and their Applications,' Adam Hilger, Bristol, 1989
6 M. Yannakakis, 'Node deletion problems on bipartite graphs,' SIAM J. Comput, Vol.10, pp.310-327, 1981   DOI
7 L. A. Zadeh, 'Fuzzy Sets and their Applications to Pattern Classification and Clustering Analysis Classification and Clustering,' Academic Press, New York, 1977
8 M. Maddouri, S. Elldumi, Jaoua A, 'An Incremental Learning System for Imprecise and Uncertain Knowledge Discovery,' Information Sciences, Vol.109, pp.149-164, 1998   DOI   ScienceOn
9 D. S. Hochbaum, 'Approximating Clique and Biclique Problems,' Journal of Algorithm, Vol.29, pp.174-200, 1998   DOI   ScienceOn
10 R. Khcherif, A. Jaoua, 'Rectangular Decomposition Heuristics for Documentary Databases,' Information Sciences, Vol.102, pp.187-202, 1997   DOI   ScienceOn
11 Morton Nadler, Eric P.Smith, 'Pattern Recognition Engineering,' John Wiley and Sons, pp.341-344, 1997
12 D. S. Hochbaum, 'Approximating Clique and Biclique Problems,' Journal of Algorithms. Vol.29, pp.174-200, 1998   DOI   ScienceOn
13 H. Ishibuchi, K. Nozaki, H. Tanaka, 'Effective fuzzy partition of pattern space for classification problems,' Fuzzy Sets and Systems, Vol.59, pp.295-304, 1993   DOI   ScienceOn
14 Jang, D.-S., Choi, H. I., 'Automatic Generation of Fuzzy Rules with Fuzzy Associative Memory,' Proceeding of the ISCA 5th International Conference, pp.182-186, 1996
15 M. Maddouri, A. Jaoua, 'Comparative empirical evaluation of the discovered knowledge,' Proceeding of the IEA/AIE'97 10th International Conference, pp.7-10, 1997
16 S. M. Weiss, C. A. Kulikowski, 'Computer Systems that Learn,' Morgan Kaufmann, Los Altos, CA, 1991