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...
Despite the existence of obstacles in many database applications, traditional spatial query processing utilizes the Euclidean distance metric assuming that points in space are dire...
Jun Zhang, Dimitris Papadias, Kyriakos Mouratidis,...
Approximate Nearest Neighbor (ANN) methods such as Locality Sensitive Hashing, Semantic Hashing, and Spectral Hashing, provide computationally ecient procedures for nding objects...
Nearest neighbor (NN) classification assumes locally constant class conditional probabilities, and suffers from bias in high dimensions with a small sample set. In this paper, we p...
In this paper we show how the complexity of performing nearest neighbor (NNS) search on a metric space is related to the expansion of the metric space. Given a metric space we loo...