Intent boundary segmentation for multi-intent utterances

A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a data processing system, causes the data processing system to implement an abnormal entity detection mechanism that facilitates detecting abnormal entities in real-time response systems through weak supervision, and further causes the data processing system to:

• responsive to identifying one or more possible intents in an utterance from real-time chat information from a real-time chat session, for each term of a set of terms in the utterance, generate a set of adversarial utterances for the utterance;
• determine an influence of changing each term by:
• determining a meaning of the utterance without the alternative term;
• determining a meaning of the utterance with the alternative term;
• and
• comparing the meaning of the utterance without the alternative term to the meaning of the utterance with the alternative term so as identify a term importance value;
• utilizing the term importance value of each term in the set of terms in the utterance, identify one or more of a change in ranking of the intent of the utterance or a change in confidence with regard to the intent of the utterance;
• utilizing the term importance value for each term in the set of terms in the utterance, perform entropy-based segmentation of the utterance into a plurality of candidate partitions;
• assign an associated intent based on ranking and confidence and entropy value to each segment of the utterance based on a sum of term importance values of the terms in the respective segment;
• and
• based on a segment with minimum entropy, direct a call associated with the real-time chat session to an operation associated with the associated intent of the segment with minimum entropy.

An apparatus comprising:

• at least one processor;
• and
• at least one memory coupled to the at least one processor, wherein the at least one memory comprises instructions which, when executed by the at least one processor, cause the at least one processor to implement an abnormal entity detection mechanism that facilitates detecting abnormal entities in real-time response systems through weak supervision, and further cause the at least one processor to:
• responsive to identifying one or more possible intents in an utterance from real-time chat information from a real-time chat session, for each term of a set of terms in the utterance, generate a set of adversarial utterances for the utterance;
• determine an influence of changing each term by:
• determining a meaning of the utterance without the alternative term;
• determining a meaning of the utterance with the alternative term;
• and
• comparing the meaning of the utterance without the alternative term to the meaning of the utterance with the alternative term so as identify a term importance value;
• utilizing the term importance value of each term in the set of terms in the utterance, identify one or more of a change in ranking of the intent of the utterance or a change in confidence with regard to the intent of the utterance;
• utilizing the term importance value for each term in the set of terms in the utterance, perform entropy-based segmentation of the utterance into a plurality of candidate partitions;
• assign an associated intent based on ranking and confidence and entropy value to each segment of the utterance based on a sum of term importance values of the terms in the respective segment;
• and
• based on a segment with minimum entropy, direct a call associated with the real-time chat session to an operation associated with the associated intent of the segment with minimum entropy.