TY - GEN
T1 - BV-RSA
T2 - 12th International Conference on Service Systems and Service Management, ICSSSM 2015
AU - Li, Hong
AU - Lin, Hao
AU - Wu, Junjie
AU - Cheng, Gong
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/7/28
Y1 - 2015/7/28
N2 - There are two key issues in applying simulated annealing method to solve the problem of ensemble clustering. One is improving the solution quality as much as possible, the other is accelerating the annealing process, thus obtain the solution rapidly. Aiming at solving the two questions, a rapid simulated annealing model for ensemble clustering, called BV-RSA, is presented. In BV-RSA, the partial consensus of basic partitions is used as important heuristic information, data objects with consensus cluster label in basic partitions are controlled moving in a group way, and their moving directions are decided by the positive-negative voting, thus reduce the randomness of object moving and speed up the clustering behavior in annealing process. Experiments on real world data set demonstrate that under any initial state, BV-RSA model performance well both in convergence and robustness.
AB - There are two key issues in applying simulated annealing method to solve the problem of ensemble clustering. One is improving the solution quality as much as possible, the other is accelerating the annealing process, thus obtain the solution rapidly. Aiming at solving the two questions, a rapid simulated annealing model for ensemble clustering, called BV-RSA, is presented. In BV-RSA, the partial consensus of basic partitions is used as important heuristic information, data objects with consensus cluster label in basic partitions are controlled moving in a group way, and their moving directions are decided by the positive-negative voting, thus reduce the randomness of object moving and speed up the clustering behavior in annealing process. Experiments on real world data set demonstrate that under any initial state, BV-RSA model performance well both in convergence and robustness.
KW - Ensemble clustering
KW - consensus clustering
KW - simulated annealing
KW - voting
UR - https://www.scopus.com/pages/publications/84948138149
U2 - 10.1109/ICSSSM.2015.7170345
DO - 10.1109/ICSSSM.2015.7170345
M3 - 会议稿件
AN - SCOPUS:84948138149
T3 - 2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015
BT - 2015 12th International Conference on Service Systems and Service Management, ICSSSM 2015
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 22 June 2015 through 24 June 2015
ER -