Systematic derivation of bounds and glue constraints for time-series constraints

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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.

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Arafailova, E., Beldiceanu, N., Carlsson, M., Flener, P., Francisco Rodríguez, M. A., Pearson, J., & Simonis, H. (2016). Systematic derivation of bounds and glue constraints for time-series constraints. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9892 LNCS, pp. 13–29). Springer Verlag. https://doi.org/10.1007/978-3-319-44953-1_2

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