… is to partition a set of objects into clusters such that the number of … correlation clustering and
user interaction. More specifically, we allow the user to control the quality of the clustering by …

… We will define the correlation clustering objective used throughout the remainder of the
paper, the domain of the vertices and cluster features used to express existential cluster …

… ) clustering methods are less helpful. This article provides a comprehensive review of
interactive clustering … , they evaluated the computed splits using the correlation-clustering error. …

… in the interactive clustering area. Interactive clustering has been applied to leverage the
strengths of both unsupervised and supervised learning. In interactive clustering, supervised …

… clustering with overclustering error δo and underclustering error δu, we present interactive
clustering … To efficiently find the target clustering with respect to the correlation clustering error, …

… Specifically, it includes: (1) an interactive feature selection method for identifying potentially
… ) an interactive, hierarchical clustering method for searching multivariate clusters of arbitrary …

… clustering, and repeat these two steps until a satisfactory result is obtained. Such an interactive
clustering process requires the clustering … reasonable (intermediate) clustering to the user …

… Clustering is a fundamental task in unsupervised learning. The focus of this paper is the
Correlation Clustering … 3 provides an example of our novel interactive multi-object segmentation …

… We test our algorithms on synthetic and real data from the domains of social media,
protein-interaction networks, and bibliometrics. Results reveal that our algorithms outperform a …

… visualization techniques to derive data clusters in a completely interactive and visual way. In
… , unsupervised clustering algorithms and Section 19.4 discusses the interactive comparison …