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Systematic Derivation of Bounds and Glue Constraints for Time-Series Constraints

  • Ekaterina ArafailovaEmail author
  • Nicolas Beldiceanu
  • Mats Carlsson
  • Pierre Flener
  • María Andreína Francisco Rodríguez
  • Justin Pearson
  • Helmut Simonis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9892)

Abstract

Integer time series are often subject to constraints on the aggregation of the integer features of all occurrences of some pattern within the series. For example, the number of inflexions may be constrained, or the sum of the peak maxima, or the minimum of the peak widths. It is currently unknown how to maintain domain consistency efficiently on such constraints. We propose parametric ways of systematically deriving glue constraints, which are a particular kind of implied constraints, as well as aggregation bounds that can be added to the decomposition of time-series constraints [5]. We evaluate the beneficial propagation impact of the derived implied constraints and bounds, both alone and together.

Keywords

Time Series Absolute Difference Regular Expression Signature Constraint Deterministic Finite Automaton 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Ekaterina Arafailova
    • 1
    Email author
  • Nicolas Beldiceanu
    • 1
  • Mats Carlsson
    • 2
  • Pierre Flener
    • 3
  • María Andreína Francisco Rodríguez
    • 3
  • Justin Pearson
    • 3
  • Helmut Simonis
    • 4
  1. 1.TASC (CNRS/Inria), Mines NantesNantesFrance
  2. 2.SICSKistaSweden
  3. 3.Department of Information TechnologyUppsala UniversityUppsalaSweden
  4. 4.Insight Centre for Data AnalyticsUniversity College CorkCorkIreland

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