Temporal probabilistic object bases

Veronica Biazzo; Rosalba Giugno; Thomas Lukasiewicz; V. S. Subrahmanian

doi:10.1109/TKDE.2003.1209009

Temporal probabilistic object bases

Veronica Biazzo^*, Rosalba Giugno, Thomas Lukasiewicz, V. S. Subrahmanian

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

There are numerous applications where we have to deal with temporal uncertainty associated with objects. The ability to automatically store and manipulate time, probabilities, and objects is important. We propose a data model and algebra for temporal probabilistic object bases (TPOBs), which allows us to specify the probability with which an event occurs at a given time point. In explicit TPOB-instances, the sets of time points along with their probability intervals are explicitly enumerated. In implicit TPOB-instances, sets of time points are expressed by constraints and their probability intervals by probability distribution functions. Thus, implicit object base instances are succinct representations of explicit ones; they allow for an efficient implementation of algebraic operations, while their explicit counterparts make defining algebraic operations easy. We extend the relational algebra to both explicit and implicit instances and prove that the operations on implicit instances correctly implement their counterpart on explicit instances.

Original language	English (US)
Pages (from-to)	921-939
Number of pages	19
Journal	IEEE Transactions on Knowledge and Data Engineering
Volume	15
Issue number	4
DOIs	https://doi.org/10.1109/TKDE.2003.1209009
State	Published - Jul 2003
Externally published	Yes

Funding

The authors would like to thank the reviewers for their excellent comments that greatly improved the paper. This work has been funded by ARL contract DAAL0197K0135, ARO grant DAAD190010484, DARPA/RL contract F306029910552, the ARL ADA CTA, US National Science Foundation (NSF) grant 937756, US NSF grant 01-5-24115, the Austrian Science Fund under project Z29-INF, a DFG grant, and a Marie Curie Individual Fellowship of the European Community programme “Human Potential” under contract number HPMF-CT-2001-001286 (disclaimer: The authors are solely responsible for information communicated and the European Commission is not responsible for any views or results expressed).

Keywords

Probabilistic databases
Temporal data
Uncertainty management

ASJC Scopus subject areas

Information Systems
Computer Science Applications
Computational Theory and Mathematics

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10.1109/TKDE.2003.1209009

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title = "Temporal probabilistic object bases",

abstract = "There are numerous applications where we have to deal with temporal uncertainty associated with objects. The ability to automatically store and manipulate time, probabilities, and objects is important. We propose a data model and algebra for temporal probabilistic object bases (TPOBs), which allows us to specify the probability with which an event occurs at a given time point. In explicit TPOB-instances, the sets of time points along with their probability intervals are explicitly enumerated. In implicit TPOB-instances, sets of time points are expressed by constraints and their probability intervals by probability distribution functions. Thus, implicit object base instances are succinct representations of explicit ones; they allow for an efficient implementation of algebraic operations, while their explicit counterparts make defining algebraic operations easy. We extend the relational algebra to both explicit and implicit instances and prove that the operations on implicit instances correctly implement their counterpart on explicit instances.",

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Temporal probabilistic object bases

Abstract

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Keywords

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