Database Repairing and Consistent Query Answering

Bertossi, Leopoldo

doi:10.1007/978-3-031-01883-1

Cited by 97 publications

(10 citation statements)

References 103 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…constants) in q. Constraints Our framework will also employ denial constraints (DCs) (Bertossi 2011;Fan and Geerts 2012). A denial constraint over a schema S takes the form ∃⃗ y.φ(⃗ y) → ⊥, where φ(⃗ y) is a Boolean CQ with inequalities, whose relational atoms use relation symbols from S. We impose the standard safety condition: each variable occurring in an inequality atom must also occur in some relational atom.…”

Section: Preliminariesmentioning

confidence: 99%

LACE: A Logical Approach to Collective Entity Resolution

Cima

Gutiérrez-Basulto

2022

Proceedings of the 41st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems

View full text Add to dashboard Cite

In this paper, we revisit the problem of entity resolution and propose a novel, logical framework, LACE, which mixes declarative and procedural elements to achieve a number of desirable properties. Our approach is fundamentally declarative in nature: it utilizes hard and soft rules to specify conditions under which pairs of entity references must or may be merged, together with denial constraints that enforce consistency of the resulting instance. Importantly, however, rule bodies are evaluated on the instance resulting from applying the already 'derived' merges. It is the dynamic nature of our semantics that enables us to capture collective entity resolution scenarios, where merges can trigger further merges, while at the same time ensuring that every merge can be justified. As the denial constraints restrict which merges can be performed together, we obtain a space of (maximal) solutions, from which we can naturally define notions of certain and possible merges and query answers. We explore the computational properties of our framework and determine the precise computational complexity of the relevant decision problems. Furthermore, as a first step towards implementing our approach, we demonstrate how we can encode the various reasoning tasks using answer set programming.

show abstract

Section: Preliminariesmentioning

confidence: 99%

LACE: A Logical Approach to Collective Entity Resolution

Cima

Gutiérrez-Basulto

2022

Proceedings of the 41st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems

View full text Add to dashboard Cite

show abstract

“…There are connections between database causality and consistency-based diagnosis and abductive diagnosis, that are two forms of model-based diagnosis [31,8]. There are also connections with database repairs [2,3]. These connections have led to complexity and algorithmic results for causality and responsibility [4,5] (see Section 4).…”

Section: Causal Responsibilitymentioning

confidence: 99%

“…In this section we will first establish a useful connection between database repairs and causes as tuples in a database [2,3]. The notion of repair of a relational database was introduced in order to formalize the notion of consistent query answering (CQA), as shown in Figure 1: If a database D is inconsistent in the sense that is does not satisfy a given set of integrity constraints, ICs, and a query Q is posed to D (left-hand side of Figure 1), what are the meaningful, or consistent, answers to Q from D?…”

Section: The Database Repair Connectionmentioning

confidence: 99%

See 1 more Smart Citation

Characterizing and Computing Causes for Query Answers in Databases from Database Repairs and Repair Programs

Bertossi

2018

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

A correspondence between database tuples as causes for query answers in databases and tuple-based repairs of inconsistent databases with respect to denial constraints has already been established. In this work, answerset programs that specify repairs of databases are used as a basis for solving computational and reasoning problems about causes. Here, causes are also introduced at the attribute level by appealing to a both null-based and attributebased repair semantics. The corresponding repair programs are presented, and they are used as a basis for computation and reasoning about attribute-level causes. They are extended to deal with the case of causality under integrity constraints. Several examples with the DLV system are shown.

show abstract

“…My warmest thanks go to my wife, Jennifer, and my daughter, Paloma, for all the support, patience, and love I have received from them during all the time, several years by now, that I have spent doing research in the area. Leopoldo Bertossi August 2011…”

Section: Acknowledgmentsmentioning

confidence: 99%