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Proceedings Paper

A possibility-theory-based model for relational databases containing uncertain attribute values
Author(s): Li Li
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Paper Abstract

In this paper, we have presented an uncertain database model based on possibility certainty. The idea is to associate every candidate value (or disjunction of such values) representing an ill-known piece of data with a degree expressing the extent to which the candidate value (or disjunction) is certain. We have extended relational algebra in this context and shown that the model constitutes a strong representation system for this set of operators. The only constraints concerns (i) the join which has to be based on an equality condition, (ii) the union, Cartesian product, and join operations which must take independent relations as arguments. An important result is that the data complexity of these operations is the same as in the classical database case.

Paper Details

Date Published: 13 March 2013
PDF: 7 pages
Proc. SPIE 8784, Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies, 87840J (13 March 2013); doi: 10.1117/12.2013804
Show Author Affiliations
Li Li, China Institute of Defense Science and Technology (China)


Published in SPIE Proceedings Vol. 8784:
Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies
Yulin Wang; Liansheng Tan; Jianhong Zhou, Editor(s)

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