A5015753842- Semantic Web and Ontologies
- Advanced Database Systems and Queries
- Logic, Reasoning, and Knowledge
- Data Quality and Management
- Data Management and Algorithms
- Bayesian Modeling and Causal Inference
- Explainable Artificial Intelligence (XAI)
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Carleton University
2012-2025
San Sebastián University
2024
Millennium Institute
2021-2023
Adolfo Ibáñez University
2017-2022
Millennium Institute for Integrative Biology
2020-2022
University of Manchester
2008
Ollscoil na Gaillimhe – University of Galway
2008
Enterprise Ireland
2008
Universität Innsbruck
2008
National and Kapodistrian University of Athens
2008
Article Free Access Share on Consistent query answers in inconsistent databases Authors: Marcelo Arenas Pontificia Universidad Católica de Chile, Escuela Ingeniería, Departamento Ciencia Computación, Casilla 306, Santiago 22, Chile ChileView Profile , Leopoldo Bertossi Jan Chomicki Monmouth University, Department of Computer Science, West Long Branch, NJ NJView Authors Info & Claims PODS '99: Proceedings the eighteenth ACM SIGMOD-SIGACT-SIGART symposium Principles database systemsMay 1999...
For several reasons databases may become inconsistent with respect to a given set of integrity constraints (ICs): (a) The DBMS have no mechanism maintain certain classes ICs. (b) New are imposed on preexisting, legacy data. (c) ICs soft, user, or informational that considered at query time, but without being necessarily enforced. (d) Data from different and autonomous sources integrated, in particular mediator-based approaches.
A relational database is inconsistent if it does not satisfy a given set of integrity constraints. Nevertheless, likely that most the data in consistent with In this paper we apply logic programming based on answer sets to problem retrieving information from possibly database. Since persists original every its minimal repairs, approach specification repairs using disjunctive programs exceptions, whose semantics can be represented and computed by systems implement stable model semantics....
Integrity constraints are semantic conditions that a database should satisfy in order to be an appropriate model of external reality. In practice, and for many reasons, may not those integrity constraints, reason it is said inconsistent. However, most likely, large portion the still semantically correct, sense has made precise. After having provided formal characterization consistent data inconsistent database, natural problem emerges extracting correct data, as query answers. The usually...
Matching dependencies were recently introduced as declarative rules for data cleaning and entity resolution. Enforcing a matching dependency on database instance identifies the values of some attributes two tuples, provided that other are sufficiently similar. Assuming existence functions making equal, we formally introduce process an using dependencies, chase-like procedure. We show naturally lattice structure attribute domains, partial order semantic domination between instances. Using...
In this article we review the main concepts around database repairs and consistent query answering, with emphasis on tracing back origin, motivation, early developments. We also describe some research directions that has spun from those original line of research. emphasize, in particular, fruitful recent connections between causality databases.
In this work, we provide some insights and develop ideas, with few technical details, about the role of explanations in Data Quality context data-based machine learning models (ML). direction, there are, as expected, roles for causality, explainable artificial intelligence . The latter area not only sheds light on models, but also data that support model construction. There is room defining, identifying, explaining errors data, particular, ML, suggesting repair actions. More generally, can...
The Causal Effect (CE) is a numerical measure of causal influence variables on observed results. Despite being widely used in many areas, only preliminary attempts have been made to use CE as an attribution score data management, the strength tuples for query answering databases. In this work, we introduce, generalize and investigate so-called Causal-Effect Score context classical probabilistic
We propose a simple definition of an explanation for the outcome classifier based on concepts from causality. compare it with previously proposed notions explanation, and study their complexity. conduct experimental evaluation two real datasets financial domain.