Konferenzpaper

Extension of the relational algebra to probabilistic complex values


AutorenlisteEiter, T; Lukasiewicz, T; Walter, M

HerausgeberlisteSchewe, KD; Thalheim, B

Jahr der Veröffentlichung2000

Seiten94-115

ZeitschriftLecture notes in computer science

Bandnummer1762

ISSN0302-9743

ISBN3-540-67100-5

Konferenz1st International Symposium on Foundations of Information and Knowledge Systems (FoIKS 2000)

VerlagSpringer

SerientitelLECTURE NOTES IN COMPUTER SCIENCE


Abstract
We present a probabilistic data model for complex values. More precisely, we introduce probabilistic complex value relations, which combine the concept of probabilistic relations with the idea of complex values in a uniform framework. We then define an algebra for querying database instances, which comprises the operations of selection, projection, renaming, join, Cartesian product, union, intersection, and difference. We finally show that most of the query equivalences of classical relational algebra carry over to our algebra on probabilistic complex value relations. Hence, query optimization techniques for classical relational algebra can easily be applied to optimize queries on probabilistic complex value relations.



Zitierstile

Harvard-ZitierstilEiter, T., Lukasiewicz, T. and Walter, M. (2000) Extension of the relational algebra to probabilistic complex values, Lecture notes in computer science (Schriftenreihe), 1762, pp. 94-115

APA-ZitierstilEiter, T., Lukasiewicz, T., & Walter, M. (2000). Extension of the relational algebra to probabilistic complex values. Lecture notes in computer science (Schriftenreihe). 1762, 94-115.



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