activity
20172021
most citedA Framework for Easing the Development of Applications Embedding Answer Set Programming

17 citations · 23 across the 4 of their papers we have counts for

collaborators

10 papers

cs.AI2021

I-DLV-sr: A Stream Reasoning System based on I-DLV

Francesco Calimeri, Marco Manna, Elena Mastria +3

We introduce a novel logic-based system for reasoning over data streams, which relies on a framework enabling a tight, fine-tuned interaction between Apache Flink and the I^2-DLV s…

cs.AI20205 cited

A Machine Learning guided Rewriting Approach for ASP Logic Programs

Elena Mastria, Jessica Zangari, Simona Perri +1

Answer Set Programming (ASP) is a declarative logic formalism that allows to encode computational problems via logic programs. Despite the declarative nature of the formalism, some…

cs.LO20201 cited

Incremental maintenance of overgrounded logic programs with tailored simplifications

Giovambattista Ianni, Francesco Pacenza, Jessica Zangari

The repeated execution of reasoning tasks is desirable in many applicative scenarios, such as stream reasoning and event processing. When using answer set programming in such conte…

cs.AI2020

DaRLing: A Datalog rewriter for OWL 2 RL ontological reasoning under SPARQL queries

Alessio Fiorentino, Jessica Zangari, Marco Manna

The W3C Web Ontology Language (OWL) is a powerful knowledge representation formalism at the basis of many semantic-centric applications. Since its unrestricted usage makes reasonin…

cs.AI2019

Precomputing Datalog evaluation plans in large-scale scenarios

Alessio Fiorentino, Nicola Leone, Marco Manna +2

With the more and more growing demand for semantic Web services over large databases, an efficient evaluation of Datalog queries is arousing a renewed interest among researchers an…

cs.AI2019

Incremental Answer Set Programming with Overgrounding

Francesco Calimeri, Giovambattista Ianni, Francesco Pacenza +2

Repeated executions of reasoning tasks for varying inputs are necessary in many applicative settings, such as stream reasoning. In this context, we propose an incremental grounding…