Answer Set Programming (ASP), that extends Datalog with powerful knowledge modeling constructs, is suitable for modeling both database-oriented applications and more complex combinatorial optimization tasks arising in decision-making. However, ASP systems were not conceived having the challenges of Big Data in mind; thus they are not applicable tout court in this new setting. This paper moves the first steps towards enabling the specification of reasoning tasks on Big Data with ASP. In particular we present our ongoing work in the direction of extending the well-known DLV system to interact in a plausible way with Big Data repositories.

First Steps towards Reasoning on Big Data with DLV

Leone, Nicola;Perri, Simona;Ricca, Francesco;Veltri, Pierfrancesco;Zangari, Jessica
2018

Abstract

Answer Set Programming (ASP), that extends Datalog with powerful knowledge modeling constructs, is suitable for modeling both database-oriented applications and more complex combinatorial optimization tasks arising in decision-making. However, ASP systems were not conceived having the challenges of Big Data in mind; thus they are not applicable tout court in this new setting. This paper moves the first steps towards enabling the specification of reasoning tasks on Big Data with ASP. In particular we present our ongoing work in the direction of extending the well-known DLV system to interact in a plausible way with Big Data repositories.
ASP; Big Data; Datalog; Computer Science (all)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/290165
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