Abstract: A system and a method for performing hierarchical domain routing and intent classification on user queries in order to improve accuracy in responding to such queries and to create smoother conversations between virtual voice assistants and users are provided. The method includes: receiving an utterance from a user; analyzing the utterance in order to make an initial determination of user intent and a confidence level that relates thereto; when the confidence level is less than a threshold, applying an artificial intelligence (AI) model that is configured to assign the received utterance to one or more domains; outputting, based on the assigned domain(s), information that prompts the user to provide additional input that relates to the user intent; receiving the additional input; and secondarily determining, based on the additional input, the user intent.

Abstract: A method may receive a text string of an utterance. A method may tokenize the utterance into a plurality of tokens. A method may transform the plurality of tokens into a plurality of feature vectors. A method may assign an entity label to each of the plurality of feature vectors. A method may resolve each feature vector of the plurality of feature vectors to a corresponding standardized value of a database query language.

Abstract: Methods and systems are described herein for improvements to identifying thematic relationships in data sets using machine learning models. In particular, the methods and systems describe a way to identify dynamic thematic relationships (e.g., thematic relationships that may change as a function of time) as a function of time.

Abstract: Methods and systems are described herein for improvements to identifying thematic relationships in data sets using machine learning models. In particular, the methods and systems describe a way to identify dynamic thematic relationships (e.g., thematic relationships that may change as a function of time) as a function of time.