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
Titolo della pubblicazione ospiteAdvances in Artificial Intelligence – IBERAMIA 2018 - 16th Ibero-American Conference on AI, Proceedings
EditorEduardo Fermé, Guillermo R. Simari, Flabio Gutiérrez Segura, José Antonio Rodríguez Melquiades
EditoreSpringer Verlag
Pagine16-28
Numero di pagine13
ISBN (stampa)9783030039271
DOI
Stato di pubblicazionePubblicato - 2018
Evento16th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2018 - Trujillo, Peru
Durata: 13 nov 201816 nov 2018

Serie di pubblicazioni

NomeLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11238 LNAI
ISSN (stampa)0302-9743
ISSN (elettronico)1611-3349

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???event.eventtypes.event.conference???16th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2018
Paese/TerritorioPeru
CittàTrujillo
Periodo13/11/1816/11/18

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