2 citations · 4 across the 12 of their papers we have counts for
12 papers
On the generic information capacity of relational schemas with a single binary relation
Benoît Groz, Jan Hidders, Nina Pardal +2
We consider database schemas consisting of a single binary relation, with key constraints and inclusion dependencies. Over this space of 20 schemas, we completely characterize when…
Sufficient Explanations in Databases and their Connections to Database Repairs
Leopoldo Bertossi, Nina Pardal
We investigate the notion of sufficient explanation, and a sufficiency-degree as attribution score for database tuples in relation to query answering. We also investigate and explo…
The KG-ER Conceptual Schema Language
Enrico Franconi, Benoît Groz, Jan Hidders +4
We propose KG-ER, a conceptual schema language for knowledge graphs that describes the structure of knowledge graphs independently of their representation (relational databases, pr…
Locally Consistent K-relations: Entailment and Axioms of Functional Dependence
Timon Barlag, Miika Hannula, Juha Kontinen +2
Local consistency arises in diverse areas, including Bayesian statistics, relational databases, and quantum foundations, and so does the notion of functional dependence. We adopt a…
Rewriting Consistent Answers on Annotated Data
Phokion G. Kolaitis, Nina Pardal, Jonni Virtema +1
We embark on a study of the consistent answers of queries over databases annotated with values from a naturally ordered positive semiring. In this setting, the consistent answers o…
Computational Complexity of Preferred Subset Repairs on Data-Graphs
Nina Pardal, Santiago Cifuentes, Edwin Pin +2
Preferences are a pivotal component in practical reasoning, especially in tasks that involve decision-making over different options or courses of action that could be pursued. In t…
The Distributional Uncertainty of the SHAP score in Explainable Machine Learning
Santiago Cifuentes, Leopoldo Bertossi, Nina Pardal +3
Attribution scores reflect how important the feature values in an input entity are for the output of a machine learning model. One of the most popular attribution scores is the SHA…
A logic-based framework for database repairs
Nicolas Fröhlich, Arne Meier, Nina Pardal +1
We introduce a general abstract framework for database repairs, where the repair notions are defined using formal logic. We distinguish between integrity constraints and so-called…
Data-graph repairs: the preferred approach
Sergio Abriola, Santiago Cifuentes, Nina Pardal +1
Repairing inconsistent knowledge bases is a task that has been assessed, with great advances over several decades, from within the knowledge representation and reasoning and the da…
Unified Foundations of Team Semantics via Semirings
Timon Barlag, Miika Hannula, Juha Kontinen +2
Semiring semantics for first-order logic provides a way to trace how facts represented by a model are used to deduce satisfaction of a formula. Team semantics is a framework for st…
On the complexity of finding set repairs for data-graphs
Sergio Abriola, Santiago Cifuentes, María Vanina Martínez +2
In the deeply interconnected world we live in, pieces of information link domains all around us. As graph databases embrace effectively relationships among data and allow processin…
An epistemic approach to model uncertainty in data-graphs
Sergio Abriola, Santiago Cifuentes, María Vanina Martínez +2
Graph databases are becoming widely successful as data models that allow to effectively represent and process complex relationships among various types of data. As with any other t…