# Interactive Error Correction in Implicative Theories

arXiv: https://arxiv.org/abs/1410.5215 · HTML: https://mlsanity.com/paper/1410.5215/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Oct 2014.

## Built on by (most cited first, 1 of 1)

- [When Can a Machine Trust a Statute? A Survival Certificate for Machine-Extracted Legal Logic](https://mlsanity.com/paper/2609.01741/) (2026)

## Abstract (arXiv)

Errors in implicative theories coming from binary data are studied. First, two classes of errors that may affect implicative theories are singled out. Two approaches for finding errors of these classes are proposed, both of them based on methods of Formal Concept Analysis. The first approach uses the cardinality minimal (canonical or Duquenne-Guigues) implication base. The construction of such a base is computationally intractable. Using an alternative approach one checks possible errors on the fly in polynomial time via computing closures of subsets of attributes. Both approaches are interactive, based on questions about the validity of certain implications. Results of computer experiments are presented and discussed.