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

Claim 0:
1. A method for enhancing predictive dialogue inferences of a machine learning-based automated dialogue system, the method comprising:
at a remote machine learning-based automated dialogue service:
sourcing, into a dedicated knowledge database, a corpus of utterance data of a subscriber to the remote machine learning-based automated dialogue service, the corpus of utterance data comprising a plurality of utterances;
identifying, by a slot extraction machine learning model executed by one or more computers, a set of one or more slot values within each of the plurality of utterances;
converting, by the one or more computers, 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, by the one or more computers, the plurality of skeleton utterances into a plurality of skeleton utterance groups based on embedding values of the plurality of skeleton utterances;
identifying, by the one or more computers, a plurality of valid slot transition pairs based on a pairwise analysis of potentially interchangeable slot values;
deriving, by the one or more computers, a plurality of slot ontology groups based on the plurality of valid slot transition pairs, wherein deriving the plurality of slot ontology groups includes:
iterating through each of the plurality of valid slot transition pairs, and
at each iteration:
determining, by the one or more computers, if slot values associated with a current slot transition pair are transitively related to slot values in one or more existing slot ontology groups,
adding, by the one or more computers, the slot values associated with the current slot transition pair to an existing slot ontology group when the slot values associated with the current slot transition pair are determined to be transitively related to slot values in the existing slot ontology group, and
forming, by the one or more computers, a new slot ontology group and incorporating the slot values associated with the current slot transition pair into the new slot ontology group when the slot values associated with the current slot transition pair are determined to not be transitively related to the slot values within the one or more existing slot ontology groups;

using, by the one or more computers, 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 operated by the machine learning-based automated dialogue service 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.