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20222025
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cs.DB2025

Combined Approximations for Uniform Operational Consistent Query Answering

Marco Calautti, Ester Livshits, Andreas Pieris +1

Operational consistent query answering (CQA) is a recent framework for CQA based on revised definitions of repairs, which are built by applying a sequence of operations (e.g., fact…

cs.DB20242 cited

Machine Learning-Augmented Ontology-Based Data Access for Renewable Energy Data

Marco Calautti, Damiano Duranti, Paolo Giorgini

Managing the growing data from renewable energy production plants for effective decision-making often involves leveraging Ontology-based Data Access (OBDA), a well-established appr…

cs.DB2023

Combined Approximations for Uniform Operational Consistent Query Answering

Marco Calautti, Ester Livshits, Andreas Pieris +1

Operational consistent query answering (CQA) is a recent framework for CQA based on revised definitions of repairs, which are built by applying a sequence of operations (e.g., fact…

cs.DB2023

Querying Data Exchange Settings Beyond Positive Queries

Marco Calautti, Sergio Greco, Cristian Molinaro +1

Data exchange, the problem of transferring data from a source schema to a target schema, has been studied for several years. The semantics of answering positive queries over the ta…

cs.DB2023

Semi-Oblivious Chase Termination for Linear Existential Rules: An Experimental Study

Marco Calautti, Mostafa Milani, Andreas Pieris

The chase procedure is a fundamental algorithmic tool in databases that allows us to reason with constraints, such as existential rules, with a plethora of applications. It takes a…

cs.DB20231 cited

The Complexity of Why-Provenance for Datalog Queries

Marco Calautti, Ester Livshits, Andreas Pieris +1

Explaining why a database query result is obtained is an essential task towards the goal of Explainable AI, especially nowadays where expressive database query languages such as Da…