Directed acyclic graph based framework for training models

Techniques for chatbots, and more particularly, to techniques for using a directed acyclic graph (DAG) based framework to build and train models. In one particular aspect, a computer implemented method is provided that includes generating, by a DAG based framework, a first model and a second model,...

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Bibliographic Details
Main Authors Pan, Crystal, Singaraju, Gautam
Format Patent
LanguageEnglish
Published 21.12.2021
Subjects
CALCULATING
COMPUTING
COUNTING
ELECTRIC COMMUNICATION TECHNIQUE
ELECTRIC DIGITAL DATA PROCESSING
ELECTRICITY
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION
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Summary:Techniques for chatbots, and more particularly, to techniques for using a directed acyclic graph (DAG) based framework to build and train models. In one particular aspect, a computer implemented method is provided that includes generating, by a DAG based framework, a first model and a second model, executing the first model for a chatbot in run-time and second model for the chatbot in design-time, collecting attributes for intent classification associated with a set of utterances with the chatbot running the first model and the second model, evaluating, using one or more metrics, performance of the first model and the second model based on an analysis of the attributes for the intent classification, determining whether the performance of the second model is improved as compared to the performance of the first model, and executing the first model or the second model for the chatbot in run-time based on the performance determination.
Bibliography:Application Number: US202016823611