Abstract: The process comprises a data-acquisition phase with the creation of a database of multicomponent digital signatures constituting fingerprints of identity documents, linked to a central server relocated relative to a primary database comprising variable textual data and images of reference identity documents. A relocated checking phase of identity documents at a checkpoint comprises the digitizing of an identity document to be checked, the creation of a fingerprint of the digitized document, the comparison of the latter with the fingerprint of a document from the fingerprint database indexed with the same reference number and the sending of a message according to the result of the comparison.

Abstract: The process comprises a data-acquisition phase with the creation of a database of multicomponent digital signatures constituting fingerprints of identity documents, linked to a central server relocated relative to a primary database comprising variable textual data and images of reference identity documents. A relocated checking phase of identity documents at a checkpoint comprises the digitising of an identity document to be checked, the creation of a fingerprint of the digitised document, the comparison of the latter with the fingerprint of a document from the fingerprint database indexed with the same reference number and the sending of a message according to the result of the comparison.

Abstract: A method for optimizing an explicative rule including constructing an explicative rule including at least one logical combination of at least one elementary conclusion, each elementary conclusion including a restriction of the domain of a variable; calculating at least one modified explicative rule optimizing the value of one or more quality indicators on a database of examples; and displaying a representation of the rules and corresponding quality indicators.

Abstract: A process for iterative construction of an explanatory model including at least one rule calculated from a plurality of experiments, each of which rules is associated with at least one indicator of the quality of a corresponding rule including determining a rule, of a set of new experiments in an application space, conducting the new experiments to obtain the corresponding results, and calculating and optionally updating indicators of quality of the rule as a function of the experiments and of corresponding results.

Abstract: An editing process for an explanatory model includes a step for producing the explanatory model in the form of a set of rules. The rules are represented by logical combinations of elementary premises, each elementary premise including a restriction of the field of the variable. The rules are also represented by a logical combination of elementary conclusions, each elementary conclusion also including a restriction of the field of a variable. The process also includes a step for modifying at least a part of the initial rules, to determine a new explanatory model. The step for modifying the rules includes modifying the restrictions of the field of the variables, and calculating the quality indicators for the rule by applying the modified set of rules to a data source called the examples basis.

Abstract: A process for iterative construction of an explanatory model including at least one rule calculated from a plurality of experiments, each of which rules is associated with at least one indicator of the quality of a corresponding rule including determining a rule, of a set of new experiments in an application space, conducting the new experiments to obtain the corresponding results, and calculating and optionally updating indicators of quality of the rule as a function of the experiments and of corresponding results.

Abstract: An editing process for an explanatory model includes a step for producing the explanatory model in the form of a set of rules. The rules are represented by logical combinations of elementary premises, each elementary premise including a restriction of the field of the variable. The rules are also represented by a logical combination of elementary conclusions, each elementary conclusion also including a restriction of the field of a variable. The process also includes a step for modifying at least a part of the initial rules, to determine a new explanatory model. The step for modifying the rules includes modifying the restrictions of the field of the variables, and calculating the quality indicators for the rule by applying the modified set of rules to a data source called the examples basis.

Abstract: A method for optimizing an explicative rule including constructing an explicative rule including at least one logical combination of at least one elementary conclusion, each elementary conclusion including a restriction of the domain of a variable; calculating at least one modified explicative rule optimizing the value of one or more quality indicators on a data database of examples; and displaying a representation of the rules and corresponding quality indicators.