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...
Abstract — New privacy regulations together with everincreasing data availability and computational power have created a huge interest in data privacy research. One major researc...
Alina Campan, Traian Marius Truta, John Miller, Ra...
We propose a hybrid, unsupervised document clustering approach that combines a hierarchical clustering algorithm with Expectation Maximization. We developed several heuristics to ...
Significant progress in clustering has been achieved by algorithms that are based on pairwise affinities between the datapoints. In particular, spectral clustering methods have ...
Numerous privacy models based on the k-anonymity property have been introduced in the last few years. While differing in their methods and quality of their results, they all focus...
Alina Campan, Traian Marius Truta, Nicholas Cooper