A Model for k-Nearest Neighbor Query Processing Cost in Multidimensional Data Space.
Journal
Inf. Process. Lett.
Journal Volume
69
Journal Issue
2
Pages
69-76
Date Issued
1999
Author(s)
Abstract
A cost model for the performance of the k-nearest neighbor query in multidimensional data space is presented. Two concepts, the regional average volume and the density function, are introduced to predict the performance for uniform and non-uniform data distributions. The experiment shows that the prediction based on this model is accurate within an acceptable range of the error in low and mid dimensions. © 1999 Elsevier Science B.V. All rights reserved.
Type
journal article