• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations
Advanced Search Include Citations | Disambiguate

DMCA

Time-Parameterized Queries in Spatio-Temporal Databases (2002)

Cached

  • Download as a PDF

Download Links

  • [www.cs.ust.hk]
  • [infolab.usc.edu]
  • [infolab.usc.edu]
  • [infolab.usc.edu]
  • [infolab.usc.edu]
  • [infolab.usc.edu]
  • [infolab.usc.edu]
  • [infolab.usc.edu]
  • [www.cs.ust.hk]

  • Other Repositories/Bibliography

  • DBLP
  • Save to List
  • Add to Collection
  • Correct Errors
  • Monitor Changes
by Yufei Tao , Dimitris Papadias
Citations:80 - 4 self
  • Summary
  • Citations
  • Active Bibliography
  • Co-citation
  • Clustered Documents
  • Version History

BibTeX

@MISC{Tao02time-parameterizedqueries,
    author = {Yufei Tao and Dimitris Papadias},
    title = {Time-Parameterized Queries in Spatio-Temporal Databases},
    year = {2002}
}

Share

Facebook Twitter Reddit Bibsonomy

OpenURL

 

Abstract

Time-parameterized queries (TP queries for short) retrieve (i) the actual result at the time that the query is issued, (ii) the validity period of the result given the current motion of the query and the database objects, and (iii) the change that causes the expiration of the result. Due to the highly dynamic nature of several spatio-temporal applications, TP queries are important both as standalone methods, as well as building blocks of more complex operations. However, little work has been done towards their efficient processing. In this paper, we propose a general framework that covers time-parameterized variations of the most common spatial queries, namely window queries, k-nearest neighbors and spatial joins. In particular, each of these TP queries is reduced to nearest neighbor search where the distance functions are def'med according to the query type. This reduction allows the application and extension of well-known branch and bound techniques to the current problem. The proposed methods can be applied with mobile queries, mobile objects or both, given a suitable indexing method. Our experimental evaluation is based on R-trees and their extensions for dynamic objects.

Keyphrases

time-parameterized query    tp query    spatio-temporal database    standalone method    mobile object    validity period    window query    current problem    dynamic object    experimental evaluation    several spatio-temporal application    spatial join    building block    general framework    suitable indexing method    actual result    neighbor search    query type    efficient processing    time-parameterized variation    complex operation    k-nearest neighbor    distance function    current motion    mobile query    common spatial query    little work    bound technique    well-known branch    dynamic nature   

Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University