In this paper we present a clustering and indexing paradigm called Clindex for high-dimensional search spaces. The scheme is designed for approximate similarity searches, where on...
Chen Li, Edward Y. Chang, Hector Garcia-Molina, Gi...
We consider approaches for exact similarity search in a high dimensional space of correlated features representing image datasets, based on principles of clustering and vector qua...
We provide evidence that non-linear dimensionality reduction, clustering and data set parameterization can be solved within one and the same framework. The main idea is to define ...
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
Using visualization techniques to explore and understand high-dimensional data is an efficient way to combine human intelligence with the immense brute force computation power ava...