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19th International Conference on Data Engineering (ICDE'03)
A Heuristic for Refresh Policy Selection in Heterogeneous Environments
Bangalore, India
March 05-March 08
ISBN: 0-7803-7665-X
ASCII Text
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Henrik Engstr?, Sharma Chakravarthy, Brian Lings, "A Heuristic for Refresh Policy Selection in Heterogeneous Environments," Data Engineering, International Conference on, pp. 674, 19th International Conference on Data Engineering (ICDE'03), 2003.
 
 
BibTex
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@article{ 10.1109/ICDE.2003.1260831,
author = {Henrik Engstr? and Sharma Chakravarthy and Brian Lings},
title = {A Heuristic for Refresh Policy Selection in Heterogeneous Environments},
journal ={Data Engineering, International Conference on},
volume = {0},
year = {2003},
issn = {1063-6382},
pages = {674},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDE.2003.1260831},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Data Engineering, International Conference on
TI - A Heuristic for Refresh Policy Selection in Heterogeneous Environments
SN - 1063-6382
SP
EP
A1 - Henrik Engstr?,
A1 - Sharma Chakravarthy,
A1 - Brian Lings,
PY - 2003
KW - null
VL - 0
JA - Data Engineering, International Conference on
ER -
 
Henrik Engstr?, University of Sk?vde, Sweden
Sharma Chakravarthy, The University of Texas at Arlington
Brian Lings, The University of Exeter, UK
This work addresses data warehouse maintenance, i.e. how changes to autonomous sources should be detected and propagated to a warehouse. We have extended our work on source characteristics and timings relevant to single source views by exploring data integration from (multiple) heterogeneous sources. We identify relevant maintenance policies and develop a set of heuristics to guide policy choice. On the basis of empirical (testbed) experiments, we claim that resulting selections are good.
Citation:
Henrik Engstr?, Sharma Chakravarthy, Brian Lings, "A Heuristic for Refresh Policy Selection in Heterogeneous Environments," icde, pp.674, 19th International Conference on Data Engineering (ICDE'03), 2003
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