A critical problem in clustering research is the definition of a proper metric to measure distances between points. Semi-supervised clustering uses the information provided by the ...
Browsing and finding pictures in large-scale and heterogeneous collections is an important issue, most particularly for online photo sharing applications. Since such services know...
In this paper, we argue that the agglomerative clustering with vector cosine similarity measure performs poorly due to two reasons. First, the nearest neighbors of a document belo...
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
Several advanced techniques have been proposed for data clustering and many of them have been applied to gene expression data, with partial success. The high dimensionality and the...