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A comparison of spatial query processing techniques for native and parameter spaces

Published: 01 May 1990 Publication History

Abstract

Spatial queries can be evaluated in native space or in a parameter space. In the latter case, data objects are transformed into points and query objects are transformed into search regions. The requirement for different data and query representations may prevent the use of parameter-space searching in some applications. Native-space and parameter-space searching are compared in the context of a z order-based spatial access method. Experimental results show that when there is a single query object, searching in parameter space can be faster than searching in native space, if the data and query objects are large enough, and if sufficient redundancy is used for the query representation. The result is, however, less accurate than the native space result. When there are multiple query objects, native-space searching is better initially, but as the number of query objects increases, parameter space searching with low redundancy is superior. Native-space searching is much more accurate for multiple-object queries.

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cover image ACM Conferences
SIGMOD '90: Proceedings of the 1990 ACM SIGMOD international conference on Management of data
May 1990
398 pages
ISBN:0897913655
DOI:10.1145/93597
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 May 1990

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SIGMOD 90
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SIGMOD 90: SIGMOD'90
May 23 - 26, 1990
New Jersey, Atlantic City, USA

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Overall Acceptance Rate 785 of 4,003 submissions, 20%

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