no code implementations • 13 Apr 2015 • Mostafa Milani, Leopoldo Bertossi
We consider a semantic class, weakly-chase-sticky (WChS), and a syntactic subclass, jointly-weakly-sticky (JWS), of Datalog+- programs.
no code implementations • 13 Jun 2015 • Babak Salimi, Leopoldo Bertossi
Causality has been recently introduced in databases, to model, characterize and possibly compute causes for query results (answers).
no code implementations • 1 Jul 2015 • Leopoldo Bertossi, Babak Salimi
In this work we establish and investigate connections between causes for query answers in databases, database repairs wrt.
no code implementations • 25 Aug 2015 • Zeinab Bahmani, Leopoldo Bertossi, Nikolaos Vasiloglou
Entity resolution (ER), an important and common data cleaning problem, is about detecting data duplicate representations for the same external entities, and merging them into single representations.
no code implementations • 7 Feb 2016 • Zeinab Bahmani, Leopoldo Bertossi, Nikolaos Vasiloglou
Entity resolution (ER), an important and common data cleaning problem, is about detecting data duplicate representations for the same external entities, and merging them into single representations.
no code implementations • 20 Feb 2016 • Babak Salimi, Leopoldo Bertossi
In this work we further investigate connections between query-answer causality and abductive diagnosis and the view-update problem.
no code implementations • 22 Apr 2016 • Mostafa Milani, Andrea Cali, Leopoldo Bertossi
Datalog+/- is a family of ontology languages that combine good computational properties with high expressive power.
no code implementations • 6 Jun 2016 • Leopoldo Bertossi, Loreto Bravo
We propose and investigate a semantics for "peer data exchange systems" where different peers are related by data exchange constraints and trust relationships.
no code implementations • 10 Jul 2016 • Mostafa Milani, Leopoldo Bertossi
We apply the magic-sets rewriting in combination with the proposed QA algorithm for the optimization of QA over JWS programs.
no code implementations • 6 Nov 2016 • Leopoldo Bertossi, Babak Salimi
In this work we establish precise connections between QA-causality and both abductive diagnosis and the view-update problem in databases, allowing us to obtain new algorithmic and complexity results for QA-causality.
no code implementations • 21 Nov 2016 • Zeinab Bahmani, Leopoldo Bertossi
Entity resolution (ER) is about identifying and merging records in a database that represent the same real-world entity.
no code implementations • 10 Mar 2017 • Leopoldo Bertossi, Mostafa Milani
In this extended abstract we describe, mainly by examples, the main elements of the Ontological Multidimensional Data Model, which considerably extends a relational reconstruction of the multidimensional data model proposed by Hurtado and Mendelzon by means of tuple-generating dependencies, equality-generating dependencies, and negative constraints as found in Datalog+-.
no code implementations • 1 Apr 2017 • Leopoldo Bertossi, Mostafa Milani
Data quality assessment and data cleaning are context-dependent activities.
no code implementations • 17 Apr 2017 • Leopoldo Bertossi
In this work, answer-set programs that specify repairs of databases are used as a basis for solving computational and reasoning problems about causes for query answers from databases.
no code implementations • 4 Dec 2017 • Leopoldo Bertossi
In this work, answer-set programs that specify repairs of databases are used as a basis for solving computational and reasoning problems about causes.
no code implementations • 17 Mar 2018 • Leopoldo Bertossi, Georg Gottlob, Reinhard Pichler
This use of Datalog$^\pm$ is extended to give a set semantics to duplicates in Datalog$^\pm$ itself.
no code implementations • 24 Apr 2018 • Leopoldo Bertossi
We propose a generic numerical measure of inconsistency of a database with respect to a set of integrity constraints.
no code implementations • 27 Sep 2018 • Leopoldo Bertossi
We propose a generic numerical measure of the inconsistency of a database with respect to a set of integrity constraints.
no code implementations • 15 Mar 2020 • Leopoldo Bertossi, Jordan Li, Maximilian Schleich, Dan Suciu, Zografoula Vagena
We propose a simple definition of an explanation for the outcome of a classifier based on concepts from causality.
no code implementations • 28 Apr 2020 • Leopoldo Bertossi
We propose answer-set programs that specify and compute counterfactual interventions as a basis for causality-based explanations to decisions produced by classification models.
no code implementations • 24 Jul 2020 • Leopoldo Bertossi
We describe some approaches to explanations for observed outcomes in data management and machine learning.
no code implementations • 15 Nov 2020 • Leopoldo Bertossi
In relation to the outcome of the model, the resulting counterfactual entities serve as a basis for the definition and computation of causality-based explanation scores for the feature values in the entity under classification, namely "responsibility scores".
no code implementations • 16 Apr 2021 • Marcelo Arenas, Pablo Barceló, Leopoldo Bertossi, Mikaël Monet
While in general computing Shapley values is an intractable problem, we prove a strong positive result stating that the $\mathsf{SHAP}$-score can be computed in polynomial time over deterministic and decomposable Boolean circuits.
no code implementations • 19 Jun 2021 • Leopoldo Bertossi
We describe some recent approaches to score-based explanations for query answers in databases and outcomes from classification models in machine learning.
no code implementations • 21 Jul 2021 • Leopoldo Bertossi, Gabriela Reyes
We describe how answer-set programs can be used to declaratively specify counterfactual interventions on entities under classification, and reason about them.
no code implementations • 2 Aug 2021 • Leopoldo Bertossi, Mostafa Milani
We propose a bottom-up QA algorithm for programs in the class sch(S), for a general selection function S. As a particular case, we obtain a polynomial-time QA algorithm for JWS and weakly-sticky programs.
no code implementations • 19 Aug 2021 • Leopoldo Bertossi
Consistent answers to a query from a possibly inconsistent database are answers that are simultaneously retrieved from every possible repair of the database.
no code implementations • 25 Aug 2021 • Leopoldo Bertossi
There are some recent approaches and results about the use of answer-set programming for specifying counterfactual interventions on entities under classification, and reasoning about them.
no code implementations • 25 Sep 2022 • Leopoldo Bertossi
We briefly describe -- mainly through very simple examples -- different kinds of answer-set programs with annotations that have been proposed for specifying: database repairs and consistent query answering; secrecy view and query evaluation with them; counterfactual interventions for causality in databases; and counterfactual-based explanations in machine learning.
no code implementations • 6 Mar 2023 • Leopoldo Bertossi
In this expository article we highlight the relevance of explanations for artificial intelligence, in general, and for the newer developments in {\em explainable AI}, referring to origins and connections of and among different approaches.
no code implementations • 11 Mar 2023 • Leopoldo Bertossi, Jorge E. Leon
The use of Shap scores has become widespread in Explainable AI.
no code implementations • 15 Jun 2023 • Leopoldo Bertossi
We describe some recent approaches to score-based explanations for query answers in databases.
no code implementations • 31 Jul 2023 • Leopoldo Bertossi
We describe recent research on the use of actual causality in the definition of responsibility scores as explanations for query answers in databases, and for outcomes from classification models in machine learning.
no code implementations • 23 Jan 2024 • Santiago Cifuentes, Leopoldo Bertossi, Nina Pardal, Sergio Abriola, Maria Vanina Martinez, Miguel Romero
In this paper, we propose a principled framework for reasoning on SHAP scores under unknown entity population distributions.