Optimization and evaluation of database queries including embedded interpolation procedures

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Optimization and evaluation of database queries including embedded interpolation procedures

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International Conference on Management of Data archive
Proceedings of the 1991 ACM SIGMOD international conference on Management of data table of contents

Denver, Colorado, United States

Pages: 118 - 127

Year of Publication: 1991

ISBN:0-89791-425-2

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Author

Leonore Neugebauer

IPVR, University of Stuttgart

Sponsors

SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 2, Downloads (12 Months): 23, Citation Count: 6

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY 6

	Goetz Graefe, Query evaluation techniques for large databases, ACM Computing Surveys (CSUR), v.25 n.2, p.73-169, June 1993
	Philippe Rigaux , Michel Scholl , Luc Segoufin , Stéphane Grumbach, Building a constraint-based spatial database system: model, languages, and implementation, Information Systems, v.28 n.6, p.563-595, September 2003
	Amol Deshpande , Samuel Madden, MauveDB: supporting model-based user views in database systems, Proceedings of the 2006 ACM SIGMOD international conference on Management of data, June 27-29, 2006, Chicago, IL, USA
	Richard H. Wolniewicz , Goetz Graefe, Algebraic Optimization of Computations over Scientific Databases, Proceedings of the 19th International Conference on Very Large Data Bases, p.13-24, August 24-27, 1993
	Stéphane Grumbach , Philippe Rigaux , Luc Segoufin, Manipulating Interpolated Data is Easier than You Thought, Proceedings of the 26th International Conference on Very Large Data Bases, p.156-165, September 10-14, 2000
	Tingjian Ge , Stan Zdonik, A skip-list approach for efficiently processing forecasting queries, Proceedings of the VLDB Endowment, v.1 n.1, August 2008