Languages, automata, and logic
Handbook of formal languages, vol. 3
The TSQL2 Temporal Query Language
The TSQL2 Temporal Query Language
Time Granularities in Databases, Data Mining and Temporal Reasoning
Time Granularities in Databases, Data Mining and Temporal Reasoning
Introduction to Algorithms
An Algebraic Representation of Calendars
Annals of Mathematics and Artificial Intelligence
Solving multi-granularity temporal constraint networks
Artificial Intelligence
Efficiently Supporting Temporal Granularities
IEEE Transactions on Knowledge and Data Engineering
Ultimately Periodic Words of Rational w-Languages
Proceedings of the 9th International Conference on Mathematical Foundations of Programming Semantics
Calendars, Time Granularities, and Automata
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Temporalized logics and automata for time granularity
Theory and Practice of Logic Programming
Representing and Reasoning about Temporal Granularities
Journal of Logic and Computation
LTL Over integer periodicity constraints
Theoretical Computer Science
Evaluating Exceptions on Time Slices
ER '09 Proceedings of the 28th International Conference on Conceptual Modeling
Temporal aggregation on user-defined granularities
Journal of Intelligent Information Systems
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Most approaches to time granularity proposed in the literature are based on algebraic and logical formalisms [J. Euzenat, A. Montanari, Time granularity, in: M. Fisher, D. Gabbay, L. Vila (Eds.), Handbook of Temporal Reasoning in Artificial Intelligence, Elsevier, 2005, pp. 59-118]. Here we follow an alternative automaton-based approach, originally outlined in [U. Dal Lago, A. Montanari, Calendars, time granularities, and automata, in: Proceedings of the 7th International Symposium on Spatial and Temporal Databases, SSTD, in: LNCS, vol. 2121, Springer, 2001, pp. 279-298], which makes it possible to deal with infinite time granularities in an effective and efficient way. Such an approach provides a neat solution to fundamental algorithmic problems, such as the granularity equivalence and granule conversion problems, which have been often neglected in the literature. In this paper, we focus our attention on two basic optimization problems for the automaton-based representation of time granularities, namely, the problem of computing the smallest representation of a time granularity and that of computing the most tractable representation of it, that is, the one on which crucial algorithms, such as granule conversion algorithms, run fastest.