Deriving production rules for constraint maintenance
Proceedings of the sixteenth international conference on Very large databases
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ACM Transactions on Software Engineering and Methodology (TOSEM)
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VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Outlier Mining in Large High-Dimensional Data Sets
IEEE Transactions on Knowledge and Data Engineering
Minimal-change integrity maintenance using tuple deletions
Information and Computation
Outlier detection by active learning
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DEXA '06 Proceedings of the 17th International Conference on Database and Expert Systems Applications
ACM Transactions on Database Systems (TODS)
Outlier detection by logic programming
ACM Transactions on Computational Logic (TOCL)
Consistent query answering: five easy pieces
ICDT'07 Proceedings of the 11th international conference on Database Theory
Consistent query answers on numerical databases under aggregate constraints
DBPL'05 Proceedings of the 10th international conference on Database Programming Languages
Querying and repairing inconsistent XML data
WISE'05 Proceedings of the 6th international conference on Web Information Systems Engineering
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Frequent constraint violations on the data stored in a database may suggest that the represented reality is changing, and thus the database does not reflect it anymore. It is thus desirable to devise methods and tools to support (semi-)automatic schema changes, in order for the schema to mirror the new situation. In this work we propose a methodology and the RELACS tool, based on data mining, to maintain the domain and tuple integrity constraints specified at design time, in order to adjust them to the evolutions of the modeled reality that may occur during the database life. The approach we propose allows to isolate frequent and meaningful constraint violations and, consequently, to extract novel rules that can be used to update or relax the no longer up-to-date integrity constraints.