We address here two major challenges presented by dynamic data mining: 1) the stability challenge: we have implemented a rigorous incremental density-based clustering algorithm, i...
In this work we investigate the feasibility and effectiveness of unsupervised tissue clustering and classification algorithms for DTI data. Tissue clustering and classification ...
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Open answers in questionnaires contain valuable information that is very time-consuming to analyze manually. We present a method for hypothesis generation from questionnaires base...
We address the problem of the combination of multiple data partitions, that we call a clustering ensemble. We use a recent clustering approach, known as Spectral Clustering, and th...