Heuristic algorithm to raise efficiency in clustering

군집의 효율향상을 위한 휴리스틱 알고리즘

  • Published : 2009.09.30

Abstract

In this study, we developed a heuristic algorithm to get better efficiency of clustering than conventional algorithms. Conventional clustering algorithm had lower efficiency of clustering as there were no solid method for selecting initial center of cluster and as they had difficulty in search solution for clustering. EMC(Expanded Moving Center) heuristic algorithm was suggested to clear the problem of low efficiency in clustering. We developed algorithm to select initial center of cluster and search solution systematically in clustering. Experiments of clustering are performed to evaluate performance of EMC heuristic algorithm. Squared-error of EMC heuristic algorithm showed better performance for real case study and improved greatly with increase of cluster number than the other ones.

Keywords

References

  1. 강창완, 강현철, 데이터마이닝, 사이플러스, (2007)
  2. 박우창, 승현우, 용환승, 최기헌, 데이터마이닝 개념 및 기법, 자유아카데미, (2004)
  3. 허준, 정규상, 허수희, 최희경, Clementine 7 매뉴얼, 데이터 솔루션, (2003)
  4. Kanungo, T., Mount, D.M., Netanyahu, N.S., Piatko, C.D., Silverman, R. and Wu, A.Y., An efficient k-means clustering algorithm: analysis and implementation, Pattern Analysis and Machine Intelligence, 24 (2002):881-892 https://doi.org/10.1109/TPAMI.2002.1017616
  5. K.S. Al-sultan, A tabu search approach to the clustering problem, Pattern Recognition, 28 (1995) : 1443–1451 https://doi.org/10.1016/0031-3203(95)00022-R
  6. Ordonez, C., Integrating K-means clustering with a relational DBMS using SQL, Knowledge and Data Engineering, 18 (2006) : 188 - 201 https://doi.org/10.1109/TKDE.2006.31
  7. Resnick, P., N. Iacovou, M. Suchak, P. Bergstrom and J. Riedl, Grouplens : An Open Architecture for Collaborative Filtering of Netnews, Proceedings of the ACM Conf. on Computer Supported Cooperative Work (1994), 175-186 https://doi.org/10.1145/192844.192905
  8. SPSS, Clementine 8.0 user's guide, SPSS, (2003)
  9. Temel Oncan, Jean-Francois Cordeau and Gilbert Laporte, A tabu search heuristic for the generalized minimum spanning tree problem, European Journal of Operational Research, 191 (2008) : 306–319 https://doi.org/10.1016/j.ejor.2007.08.021
  10. Yongguo Liu, Zhang Yi, Hong Wua, Mao Ye and Kefei Chen, A tabu search approach for the minimum sum-of-squares clustering problem, Information Sciences,178 (2008) : 2680–2704 https://doi.org/10.1016/j.ins.2008.01.022