Systems, Man, and Cybernetics

 

Home

• [P729] Active constrained clustering with multiple cluster representatives
  Author(s): Shaohong Zhang, Hau-San Wong
  
  

  Abstract
  Constrained clustering has recently become an active topic. This type of clustering methods makes advantage of partial knowledge in the form of pairwise constraints and acquires significant improvement beyond the traditional unsupervised clustering. However, most of the existing constrained clustering methods use the constraints which are selected at random. Recently active constrained clustering algorithms utilizing active constraints are proved to have more effectiveness and more efficiency. In this paper, we propose an improved algorithm which introduces multiple representatives into constrained clustering to make further use of the active constraints. Experiments on several benchmark data sets and public image data sets demonstrate the advantages of our algorithm over the referenced competitors.

  
   

Full Text (PDF)