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SIGMOD
2006
ACM
127views Database» more  SIGMOD 2006»
15 years 10 months ago
Efficient reverse k-nearest neighbor search in arbitrary metric spaces
The reverse k-nearest neighbor (RkNN) problem, i.e. finding all objects in a data set the k-nearest neighbors of which include a specified query object, is a generalization of the...
Elke Achtert, Christian Böhm, Peer Kröge...
124
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JPDC
2007
138views more  JPDC 2007»
14 years 9 months ago
Distributed computation of the knn graph for large high-dimensional point sets
High-dimensional problems arising from robot motion planning, biology, data mining, and geographic information systems often require the computation of k nearest neighbor (knn) gr...
Erion Plaku, Lydia E. Kavraki
COMPGEOM
2005
ACM
14 years 11 months ago
Fast construction of nets in low dimensional metrics, and their applications
We present a near linear time algorithm for constructing hierarchical nets in finite metric spaces with constant doubling dimension. This data-structure is then applied to obtain...
Sariel Har-Peled, Manor Mendel
COMPGEOM
2006
ACM
15 years 3 months ago
Lower bounds on locality sensitive hashing
Given a metric space (X, dX), c ≥ 1, r > 0, and p, q ∈ [0, 1], a distribution over mappings H : X → N is called a (r, cr, p, q)-sensitive hash family if any two points in...
Rajeev Motwani, Assaf Naor, Rina Panigrahy
MMM
2011
Springer
251views Multimedia» more  MMM 2011»
14 years 1 months ago
Randomly Projected KD-Trees with Distance Metric Learning for Image Retrieval
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...