Title :
BV-RSA: A rapid simulated annealing model for ensemble clustering
Author :
Hong Li ; Hao Lin ; Junjie Wu ; Gong Cheng
Author_Institution :
Sch. of Econ. & Manage., Beihang Univ., Beijing, China
Abstract :
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.
Keywords :
pattern clustering; simulated annealing; BV-RSA; consensus cluster label; ensemble clustering; positive-negative voting; rapid simulated annealing model; Annealing; Clustering algorithms; Convergence; Error analysis; Linear programming; Partitioning algorithms; Simulated annealing; Ensemble clustering; consensus clustering; simulated annealing; voting;
Conference_Titel :
Service Systems and Service Management (ICSSSM), 2015 12th International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4799-8327-8
DOI :
10.1109/ICSSSM.2015.7170345