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Systems and methods for a two-tier machine learning model for generating conversational responses

專利號(hào)
US11616741B2
公開日期
2023-03-28
申請(qǐng)人
Capital One Services, LLC(US VA McLean)
發(fā)明人
Kunlaya Soiaporn; Victor Alvarez Miranda; Pamela Katali; Arturo Hernandez Zeledon; Rui Zhang; Kwan-Yuet Ho
IPC分類
H04L51/02; G06K9/62; G10L15/16; G06N20/20
技術(shù)領(lǐng)域
learning,model,intent,machine,user,may,tier,or,in,cluster
地域: VA VA McLean

摘要

Methods and systems are described for generating dynamic conversational responses using two-tier machine learning models. The dynamic conversational responses may be generated in real time and reflect the likely goals and/or intents of a user. The two-tier machine learning model may include a first tier that determines an intent cluster based on a feature input, and a second tier that determines a specific intent from the cluster.

說明書

In order to maintain the conversational interaction, the system may need to generate response (e.g., conversational response) dynamically and/or in substantially real-time. For example, the system may generate responses within the normal cadence of a conversation. In some embodiments, the system may continually determine a likely intent of the user in order to generate responses (e.g., in the form of prompts, notifications, and/or other communications) to the user. It should be noted that a response may include any step or action (or inaction) taken by the system, including computer processes, which may or may not be perceivable to a user.

For example, in response to a user action, which in some embodiments may comprise a user logging onto an application that generates user interface 100, inputting a query (e.g., query 104) into user interface 100, and/or a prior action (or lack thereof) by a user to a prior response generated by the system, the system may take one or more steps to generate dynamic conversational responses. These steps may include retrieving data about the user, retrieving data from other sources, monitoring user actions, and/or other steps in order to generate a feature input (e.g., as discussed below).

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