An experimental study of constrained clustering effectiveness in presence of erroneous constraints |
| |
Authors: | M Eduardo Ares Javier Parapar Álvaro Barreiro |
| |
Institution: | IRLab, Department of Computer Science, University of A Coruña, Campus de Elviña, 15071 A Coruña, Spain |
| |
Abstract: | Recently a new fashion of semi-supervised clustering algorithms, coined as constrained clustering, has emerged. These new algorithms can incorporate some a priori domain knowledge to the clustering process, allowing the user to guide the method. The vast majority of studies about the effectiveness of these approaches have been performed using information, in the form of constraints, which was totally accurate. This would be the ideal case, but such a situation will be impossible in most realistic settings, due to errors in the constraint creation process, misjudgements of the user, inconsistent information, etc. Hence, the robustness of the constrained clustering algorithms when dealing with erroneous constraints is bound to play an important role in their final effectiveness. |
| |
Keywords: | Algorithms Clustering Constrained clustering Erroneous constraints Experimentation |
本文献已被 ScienceDirect 等数据库收录! |
|