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2005
Springer

Using the k-Nearest Neighbor Graph for Proximity Searching in Metric Spaces

9 years 9 months ago
Using the k-Nearest Neighbor Graph for Proximity Searching in Metric Spaces
Proximity searching consists in retrieving from a database, objects that are close to a query. For this type of searching problem, the most general model is the metric space, where proximity is defined in terms of a distance function. A solution for this problem consists in building an offline index to quickly satisfy online queries. The ultimate goal is to use as few distance computations as possible to satisfy queries, since the distance is considered expensive to compute. Proximity searching is central to several applications, ranging from multimedia indexing and querying to data compression and clustering. In this paper we present a new approach to solve the proximity searching problem. Our solution is based on indexing the database with the knearest neighbor graph (knng), which is a directed graph connecting each element to its k closest neighbors. We present two search algorithms for both range and nearest neighbor queries which use navigational and metrical features of the knng...
Rodrigo Paredes, Edgar Chávez
Added 28 Jun 2010
Updated 28 Jun 2010
Type Conference
Year 2005
Where SPIRE
Authors Rodrigo Paredes, Edgar Chávez
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