Patent ID: 11934794
Assignee: KNOWBL INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 18:
19. A computer-program product embodied in a non-transitory machine-readable storage medium storing computer instructions that, when executed by one or more processors, perform operations comprising:
sourcing, into a dedicated knowledge database, a corpus of utterance data of a subscriber, the corpus of utterance data comprising a plurality of utterances;
identifying, by a slot extraction machine learning model, a set of one or more slot values within each of the plurality of utterances;
converting the plurality of utterances to a plurality of skeleton utterances by masking the set of one or more slot values identified within each of the plurality of utterances, wherein masking the set of one or more slot values includes replacing each identified slot value of the set of one or more slot values with a random slot variable;
grouping the plurality of skeleton utterances into a plurality of skeleton utterance groups based on embedding values of the plurality of skeleton utterances;
identifying a plurality of valid slot transition pairs based on a pairwise analysis of potentially interchangeable slot values;
deriving a plurality of slot ontology groups based on the plurality of valid slot transition pairs;
using the plurality of slot ontology groups and the plurality of skeleton utterances to configure the dedicated knowledge database, wherein configuring the dedicated knowledge database includes:
automatically encoding the dedicated knowledge database with a plurality of metadata transition values between distinct pairs of utterances of the plurality of utterances that digitally associates each of the distinct pairs of utterances as likely transitions in a given dialogue session between a user and an automated dialogue system based on the plurality of slot ontology groups; and

once encoded, implementing the dedicated knowledge database in a production environment that enables an execution of the automated dialogue system in a plurality of automated conversations using the plurality of metadata transition values of the dedicated knowledge base to automatically predict transitionary responses based on user utterances in multi-turn conversations that likely include a change in dialogue intents;
wherein the automated dialogue system is configured to (i) compute a likely dialogue intent for each user utterance received from the user and (ii) extract slot values from each user utterance received from the user, and
using the plurality of slot ontology groups to generate a response to a subsequent user utterance received from the user includes:
identifying the likely dialogue intent of a user utterance preceding the subsequent user utterance,
generating a plurality of semantic follow-up candidate utterances based on one or more slot ontology groups associated with the user utterance preceding the subsequent user utterance,
computing a plurality of classification scores for each of the plurality of semantic follow-up candidate utterances, the plurality of utterances, and at least a subset of the plurality of skeleton utterances, and
generating a response to the subsequent user utterance based on a highest classification score among the plurality of classification scores.