Embedding forecast operators in databases

Francesco Parisi*, Amy Sliva, V. S. Subrahmanian

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Though forecasting methods are used in numerous fields, we have seen no work on providing a general theoretical framework to build forecast operators into temporal databases. In this paper, we first develop a formal definition of a forecast operator as a function that satisfies a suite of forecast axioms. Based on this definition, we propose three families of forecast operators called deterministic, probabilistic, and possible worlds forecast operators. Additional properties of coherence, monotonicity, and fact preservation are identified that these operators may satisfy (but are not required to). We show how deterministic forecast operators can always be encoded as probabilistic forecast operators, and how both deterministic and probabilistic forecast operators can be expressed as possible worlds forecast operators. Issues related to the complexity of these operators are studied, showing the relative computational tradeoffs of these types of forecast operators. Finally, we explore the integration of forecast operators with standard relational operators in temporal databases and propose several policies for answering forecast queries.

Original languageEnglish (US)
Title of host publicationScalable Uncertainty Management - 5th International Conference, SUM 2011, Proceedings
Pages373-386
Number of pages14
DOIs
StatePublished - 2011
Externally publishedYes
Event5th International Conference on Scalable Uncertainty Management, SUM 2011 - Dayton, OH, United States
Duration: Oct 10 2011Oct 13 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6929 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Conference on Scalable Uncertainty Management, SUM 2011
Country/TerritoryUnited States
CityDayton, OH
Period10/10/1110/13/11

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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