Hierarchical spatial data structures provide a means for organizing data for efficient processing. Most spatial data structures are optimized for performing queries, such as inters...
Elena Jakubiak Hutchinson, Sarah F. Frisken, Ronal...
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...
In this paper, we study weak {proximity drawings. All known algorithms that compute (weak) proximity drawings produce representations whose area increases exponentiallywith the nu...
—A novel method CLOSS intended for textual databases is proposed. It successfully identifies misspelled string clusters, even if the cluster border is not prominent. The method ...
This research-in-progress paper presents a new approach called Link Proximity Analysis (LPA) for identifying related web pages based on link analysis. In contrast to current techni...