Complexity and Approximation of Fixing Numerical Attributes in Databases Under Integrity Constraints

Bertossi, Leopoldo; Bravo, Loreto; Franconi, Enrico; Lopatenko, Andrei

doi:10.1007/11601524_17

Cited by 39 publications

(56 citation statements)

References 19 publications

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“…In [11,14,37,45,58,59] minimality associated to repairs is based on the cardinality of the set of updates, i.e. changes of attributes values (as opposed to whole tuples).…”

Section: Discussionmentioning

confidence: 99%

“…That is, for each adorned rule, the magic version of its head is inserted into the body. For instance, the magic versions of the head atoms in (11) are magic S b f b (x, f a ) and magic R b f b (x, t a ), resp., which are inserted into the body of the adorned rule, generating the modified rule: (12) From the modified rules all the adornments, except for those of the magic atoms, are now eliminated. Thus, (12) becomes:…”

mentioning

confidence: 99%

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The consistency extractor system: Answer set programs for consistent query answering in databases

Caniupan

Bertossi

2010

Data & Knowledge Engineering

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We describe the Consistency Extractor System (ConsEx) that computes consistent answers to Datalog queries with negation posed to relational databases that may be inconsistent with respect to certain integrity constraints. In order to solve this task, ConsEx uses answers set programming. More precisely, ConsEx uses disjunctive logic programs with stable models semantics to specify and reason with the repairs, i.e. with the consistent virtual instances that minimally depart from the original database. The consistent information is invariant under all repairs. ConsEx achieves efficient query evaluation by implementing magic sets techniques. We describe the general methodology, its optimizations for query answering, and the architecture of the system. We also present encouraging experimental results.

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“…In [11,14,37,45,58,59] minimality associated to repairs is based on the cardinality of the set of updates, i.e. changes of attributes values (as opposed to whole tuples).…”

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

The consistency extractor system: Answer set programs for consistent query answering in databases

Caniupan

Bertossi

2010

Data & Knowledge Engineering

Self Cite

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“…Second, we are developing effective algorithms for discovering cfd p s and cind p s, along the same lines as [10,18,15]. Third, we plan to extend the methods of [5,13] to repair data based on cfd p s and cind p s, instead of using cfds [13], traditional fds and inds [5], denial constraints [4,12], and aggregate constraints [16].…”

Section: Discussionmentioning

confidence: 99%

“…Methods have been developed for discovering cfds [10,18,15] and for repairing data based on either cfds [13], traditional fds and inds taken together [5], denial constraints [4,12], or aggregate constraints [16]. We defer the treatment of these topics for cfd p s and cind p s to future work.…”

Section: Related Workmentioning

confidence: 99%

Analyses and Validation of Conditional Dependencies with Built-in Predicates

Chen

Fan

2009

Lecture Notes in Computer Science

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Abstract. This paper proposes a natural extension of conditional functional dependencies (cfds [14]) and conditional inclusion dependencies (cinds [8]), denoted by cfd p s and cind p s, respectively, by specifying patterns of data values with =, <, ≤, > and ≥ predicates. As data quality rules, cfd p s and cind p s are able to capture errors that commonly arise in practice but cannot be detected by cfds and cinds. We establish two sets of results for central technical problems associated with cfd p s and cind p s. (a) One concerns the satisfiability and implication problems for cfd p s and cind p s, taken separately or together. These are important for, e.g., deciding whether data quality rules are dirty themselves, and for removing redundant rules. We show that despite the increased expressive power, the static analyses of cfd p s and cind p s retain the same complexity as their cfds and cinds counterparts. (b) The other concerns validation of cfd p s and cind p s. We show that given a set Σ of cfd p s and cind p s on a database D, a set of sql queries can be automatically generated that, when evaluated against D, return all tuples in D that violate some dependencies in Σ. This provides commercial dbms with an immediate capability to detect errors based on cfd p s and cind p s.

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“…These constraints differ from CFD c s in that they cannot constrain tuples with a pattern specified in terms of constants. Query answering has been investigated for aggregate queries, FDs and denial constraints [5,7], which differ from this work in that neither these dependencies can express cardinality constraints, nor the impact of cardinality constraints on the satisfiability and implication analyses has been considered.…”

Section: Introductionmentioning

confidence: 99%

Incorporating cardinality constraints and synonym rules into conditional functional dependencies

Chen

Fan

2009

Information Processing Letters

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We propose an extension of conditional functional dependencies (CFDs), denoted by CFD c s, to express cardinality constraints, domain-specific conventions, and patterns of semantically related constants in a uniform constraint formalism. We show that despite the increased expressive power, the satisfiability and implication problems for CFD c s remain NP-complete and coNP-complete, respectively, the same as their counterparts for CFDs. We also identify tractable special cases.

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Complexity and Approximation of Fixing Numerical Attributes in Databases Under Integrity Constraints

Cited by 39 publications

References 19 publications

The consistency extractor system: Answer set programs for consistent query answering in databases

The consistency extractor system: Answer set programs for consistent query answering in databases

Analyses and Validation of Conditional Dependencies with Built-in Predicates

Incorporating cardinality constraints and synonym rules into conditional functional dependencies

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