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...
The nearest neighbor (NN) classifier is well suited for generic object recognition. However, it requires storing the complete training data, and classification time is linear in ...
Ferid Bajramovic, Frank Mattern, Nicholas Butko, J...
A k-Range Nearest Neighbor (or kRNN for short) query in road networks finds the k nearest neighbors of every point on the road segments within a given query region based on the net...
Jie Bao 0003, Chi-Yin Chow, Mohamed F. Mokbel, Wei...
In high-dimensional and complex metric spaces, determining the nearest neighbor (NN) of a query object ? can be a very expensive task, because of the poor partitioning operated by...
We introduce the problem of repetitive nearest neighbor search in relevance feedback and propose an efficient search scheme for high dimensional feature spaces. Relevance feedback...