An AI Approach to Temporal Indeterminacy in Relational Databases

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Abstract

Time is pervasive of the human way of approaching reality, so that it has been widely studied in many research areas, including Artificial Intelligence (AI) and relational Temporal Databases (TDB). Indeed, while thousands of TDB papers have been devoted to the treatment of determinate time, only few approaches have faced temporal indeterminacy (i.e., “don’t know exactly when” indeterminacy). In this paper, we propose a new AI-based methodology to approach temporal indeterminacy in relational DBs. We show that typical AI techniques, such as studying the semantics of the representation formalism, and adopting symbolic manipulation techniques based on such a semantics, are very important in the treatment of indeterminate time in relational databases.
Lingua originaleInglese
Pagine16-28
Numero di pagine13
DOI
Stato di pubblicazionePubblicato - 1 gen 2018
EventoIbero-American Conference on Artificial Intelligence - Trujillo, Peru
Durata: 1 gen 2018 → …

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???event.eventtypes.event.conference???Ibero-American Conference on Artificial Intelligence
CittàTrujillo, Peru
Periodo1/01/18 → …

Keywords

  • Temporal data
  • Data representation and semantics
  • Query semantics
  • Symbolic manipulation

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