Paper Info
Title
Solving Error Correction for Large Data Sets by Means of a SAT Solver
Abstract
The paper is concerned with the problem of automatic detection and correction of erroneous data into large datasets. The adopted process should therefore be computationally efficient. As usual, errors axe here defined by using a rule-based approach: all and only the data records respecting a set of rules axe declared correct. Erroneous records should afterwards be corrected, by using as much as possible the correct information contained in them. By encoding such problem into propositional logic, for each erroneous record we have a propositional logic formula, for which we want a model having particular properties. Correction problems can therefore be quickly solved by means of a customized SAT solver. Techniques for an efficient encoding of difficult cases are presented.
Year
DOI
Venue
2003
10.1007/978-3-540-24605-3_18
Lecture Notes in Computer Science
Keywords
Field
DocType
sat solver,rule based,error correction,propositional logic
Constraint satisfaction,Data set,Computer science,Boolean satisfiability problem,Satisfiability,Propositional calculus,Algorithm,Theoretical computer science,Error detection and correction,Propositional variable,Encoding (memory)
Conference
Volume
ISSN
Citations 
2919
0302-9743
0
PageRank 
References 
Authors
0.34
8
1
Name
Order
Citations
PageRank
Renato Bruni112715.79