We present and implement an efficient algorithm for performing nearest-neighbor queries in topological spaces that usually arise in the context of motion planning. Our approach extends the Kd tree-based ANN algorithm, which was developed by Arya and Mount for Euclidean spaces. We argue the correctness of the algorithm and illustrate its efficiency through computed examples. We have applied the ...

We describe the implementation of a fast, dynamic, approximate, nearest-neighbor search algorithm that works well in fixed dimensions (d ≤ 5), based on sorting points coordinates in Morton (or z-) ordering. Our code scales well on multi-core/cpu shared memory systems. Our implementation is competitive with the best approximate nearest neighbor searching codes available on the web, especially fo...

iii Abstract A frequently encountered type of query in image database systems is to nd the k most similar images to a query image with respect to its feature. Processing such queries requires substantially diierent search algorithms than those for the normal k nearest neighbor problem: dimensionality of the feature may be very high and similarity measure may not be as simple as a Euclidean dist...

Conservative spatial queries, such as range search and nearest neighbor reclamation, involves only conditions on objects’ numerical properties. Today, many modern applications call for novel forms of queries that aim to find objects satisfying both a spatial predicate, and a predicate on their associated texts. For example, instead of considering all the restaurants, a nearest neighbor query wo...

Proximity searching is the problem of retrieving, from a given database, those objects closest to a query. To avoid exhaustive searching, data structures called indexes are built on the database prior to serving queries. The curse of dimensionality is a well-known problem for indexes: in spaces with sufficiently concentrated distance histograms, no index outperforms an exhaustive scan of the da...

K-nearest-neighbor query is an important query in uncertain network, which is finding the k close nodes to a specific node. We first put forward the concept of the credible nearest neighbor query in uncertain network, and give credible k-nearest-neighbor query algorithm. Credible distance is used to describe the distance between nodes in uncertain network. Fuzzy simulation is adopted to decreas...