Automatic identification of retraining data in a classifier-based dialogue system

A computer system for identifying data for retraining a classifier-based automatic dialogue system with recorded user interactions, the computer system comprising:

• one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising:
• receiving one or more recorded interactions, wherein the one or more recorded interactions comprise one or more inputs by a user and one or more responses by the automatic dialogue system;
• determining, based on the one or more recorded interactions, whether to pair one or more inputs with one or more classes;
• pairing, based on the one or more recorded interactions, the one or more inputs with one or more classes;
• assessing, based on the one or more recorded interactions, a reliability of the one or more paired inputs and classes;
• determining whether the one or more reliable paired inputs and classes can be consistently mapped;
• and
• merging all consistently-mapped, reliable, paired inputs and classes with an initial training set.

A computer program product for identifying data for retraining a classifier-based automatic dialogue system with recorded user interactions, the computer program product comprising:

• one or more computer-readable tangible storage medium and program instructions stored on at least one of the one or more tangible storage medium, the program instructions executable by a processor to cause the processor to perform a method comprising:
• receiving one or more recorded interactions, wherein the one or more recorded interactions comprise one or more inputs by a user and one or more responses by the automatic dialogue system;
• determining, based on the one or more recorded interactions, whether to pair one or more inputs with one or more classes;
• pairing, based on the one or more recorded interactions, the one or more inputs with one or more classes;
• assessing, based on the one or more recorded interactions, a reliability of the one or more paired inputs and classes;
• determining whether the one or more reliable paired inputs and classes can be consistently mapped;
• and
• merging all consistently-mapped, reliable, paired inputs and classes with an initial training set.