DMCA
A Model for k-Nearest Neighbor Query Cost in Multidimensional Index Structures (1998)
BibTeX
@MISC{Lee98amodel,
author = {Ju-hong Lee and Ju-hong Lee and Guang-Ho Cha and Guang-ho Cha and Chin-Wan Chung and Chin-wan Chung},
title = {A Model for k-Nearest Neighbor Query Cost in Multidimensional Index Structures},
year = {1998}
}
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Abstract
The k-nearest neighbor query in multidimensional index structures is one of the most frequently used query types in multimedia databases and geographic information systems. Until now, most of the analytic models are restricted to a particular type of the index structure, for example, the R-Tree and they concentrate on the analysis of the range query. Recently, a cost model [3] was reported for nearest neighbor queries. However, the model considered only 1-nearest neighbor queries rather than k-nearest neighbor queries. In this paper, we present an analytic model for the cost of the k-nearest neighbor query in multidimensional index structures. As a basis of the model, we introduce the concept of the regional average volume and the varying density function. The advantages of our model are in particular as follows: It is applicable to any type of datasets with arbitrary distributions (uniform and non-uniform ones), works for the k- as well as 1- nearest neighbor query, and is a dynamic a...
Keyphrases
multidimensional index structure k-nearest neighbor query cost k-nearest neighbor query neighbor query analytic model varying density function particular type range query 1-nearest neighbor query regional average volume index structure cost model non-uniform one query type arbitrary distribution geographic information system multimedia database
