2008
DOI: 10.1145/1366102.1366103
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Conditional functional dependencies for capturing data inconsistencies

Abstract: We propose a class of integrity constraints for relational databases, referred to as conditional functional dependencies (CFDs), and study their applications in data cleaning. In contrast to traditional functional dependencies (FDs) that were developed mainly for schema design, CFDs aim at capturing the consistency of data by enforcing bindings of semantically related values. For static analysis of CFDs we investigate the consistency problem , which is to determi… Show more

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Cited by 316 publications
(412 citation statements)
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References 37 publications
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“…The traditional category of methods relies on a variety of constraints including FDs [1,11], CFDs [4], Integrity Constraints [9] and Inclusion Dependencies (INCs) [1] to detect inconsistency (or conflicts) between data aroused by erroneous data, and then work on resolving all the conflicts with expecting to fix all erroneous data in this way [2,8,9]. For general textual databases, most work in this category use FD/CFDs for repairing as they are the constraints within a single relational table, while some other work uses INCs for repairing between multiple relational tables.…”
Section: Related Workmentioning
confidence: 99%
See 2 more Smart Citations
“…The traditional category of methods relies on a variety of constraints including FDs [1,11], CFDs [4], Integrity Constraints [9] and Inclusion Dependencies (INCs) [1] to detect inconsistency (or conflicts) between data aroused by erroneous data, and then work on resolving all the conflicts with expecting to fix all erroneous data in this way [2,8,9]. For general textual databases, most work in this category use FD/CFDs for repairing as they are the constraints within a single relational table, while some other work uses INCs for repairing between multiple relational tables.…”
Section: Related Workmentioning
confidence: 99%
“…So far, various data repairing solutions have been developed to automatically detect and repair erroneous data in databases [12]. The main stream of rule-based solutions [2,8,9] rely on a variety of quality rules such as FD/CFDs [1,4,11] to detect violations and conflicts between data. By resolving these violations and conflicts, they expect to fix the erroneous data.…”
Section: Introductionmentioning
confidence: 99%
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“…Extensions of functional dependencies (fds) and inclusion dependencies (inds), known as conditional functional dependencies (cfds [14]) and conditional inclusion dependencies (cinds [8]), respectively, have recently been proposed for improving data quality. These extensions enforce patterns of semantically related data values, and detect errors as violations of the dependencies.…”
Section: Introductionmentioning
confidence: 99%
“…These extensions enforce patterns of semantically related data values, and detect errors as violations of the dependencies. Conditional dependencies are able to capture more inconsistencies than fds and inds [14,8].…”
Section: Introductionmentioning
confidence: 99%