: The fuzzy c-means clustering algorithm has been widely used to obtain the fuzzy k-partitions. This algorithm requires that the user gives the number of clusters k. To find automa...
High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimension...
When a partitional structure is derived from a data set using a data mining algorithm, it is not unusual to have a different set of outcomes when it runs with a different order of...
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Clustering of high dimensional data streams is an important problem in many application domains, a prominent example being network monitoring. Several approaches have been lately ...
Irene Ntoutsi, Arthur Zimek, Themis Palpanas, Peer...