Abstract

In this paper an approach is proposed to the problem of automatic detection and correction of inconsistent or out of range data in a general process of data collecting. Such errors are usually detected by formulating a set of rules which must be respected in order the data to be declared correct. A first relevant point of the proposed procedure is that the set of rules itself is checked for inconsistency or redundancy, by encoding it in a propositional logic formula, and solving a sequence of Satisfiability problem. This set of rules is then used to detect erroneous data. In the subsequent phase of error correction, the above set of rules must be satisfied, but the erroneous data should be altered as little as possible. Moreover, the statistical distribution of correct data should be preserved. As a second relevant point, such problem is modeled by encoding the rules with linear inequalities, and solving a sequence of set covering problems. The proposed procedure is tested by performing the entire process of error detection and correction in the case of a Census.

Citations