Cluster Sculptor, an interactive visual clustering system
This paper describes Cluster Sculptor, a novel interactive clustering system that allows a user to iteratively update the cluster labels of a data set, and an associated low-dimensional projection. The system is fed by clustering results computed in a high-dimensional space, and uses a two-dimensional (2D) projection, both as support for overlaying the cluster labels, and engaging user interaction. By easily interacting with elements directly in the visualization, the user can inject his or her domain knowledge progressively. Via interactive controls, the distribution of the data in the 2D space can be used to amend the cluster labels. Reciprocally, the 2D projection can be updated so as to emphasize the current clusters. The 2D projection updates follow a smooth physical metaphor that gives insight of the process to the user. Updates can be interrupted any time, for further data inspection, or modifying the input preferences. The interest of the system is demonstrated by detailed experimental scenarios on three real data sets.
visual clustering interactive clustering dimensionality reduction