Abstract. We consider approximate nearest neighbor searching in metric spaces of constant doubling dimension. More formally, we are given a set S of n points and an error bound &g...
Sunil Arya, David M. Mount, Antoine Vigneron, Jian...
Graphs are fundamental data structures and have been employed for centuries to model real-world systems and phenomena. Random walk with restart (RWR) provides a good proximity sco...
A new access method, called M-tree, is proposed to organize and search large data sets from a generic "metric space", i.e. where object proximity is only defined by a di...
The purpose of text clustering in information retrieval is to discover groups of semantically related documents. Accurate and comprehensible cluster descriptions (labels) let the ...
Abstract. Efficient nearest neighbor (NN) search techniques for highdimensional data are crucial to content-based image retrieval (CBIR). Traditional data structures (e.g., kd-tree...
Pengcheng Wu, Steven C. H. Hoi, Duc Dung Nguyen, Y...