.png){kind=icon}
.png){kind=icon}
Return
Hierarchical constraints
.png){kind=icon}
OA
AI
DOI：10.1007/s10994-013-5397-9.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Constrained clustering received a lot of attention in the last years. However, the widely used pairwise constraints are not generally applicable for hierarchical clustering, where the goal is to derive a cluster hierarchy instead of a flat partition. Therefore, we propose for the hierarchical setting-based on the ideas of pairwise constraints-the use of must-link-before (MLB) constraints. In this paper, we discuss their properties and present an algorithm that is able to create a hierarchy by considering these constraints directly. Furthermore, we propose an efficient data structure for its implementation and evaluate its effectiveness with different datasets in a text clustering scenario.
Keywords:
Constrained clustering
Hierarchical clustering
Semi-supervised learning