- With the progress of research on cluster computing, more and more universities have begun to offer various courses covering cluster computing. A wide variety of content can be ta...
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 ...
Clustering is an essential data mining task with numerous applications. However, data in most real-life applications are high-dimensional in nature, and the related information of...
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...