Automated decisioning based on predicted user intent

A method of intent clarification and intent-based interactivity, the method comprising:

• receiving a first input through an interactive user interface, wherein the first input is associated with a first user account;
• retrieving historical first user account information associated with the first user account from a data structure based on the first input;
• parsing a first string of text corresponding to the first input using a trained machine learning model to predict an intent associated with the first user account, wherein the trained machine learning model considers the historical first user account information as context for parsing the first string of text to predict the intent, wherein the trained machine learning model includes a plurality of nodes arranged in a plurality of layers, wherein the trained machine learning model includes a plurality of connections between nodes, and wherein the plurality of connections correspond to a plurality of memory elements that store numeric weights;
• generating, based on a confidence level associated with the prediction of the intent being lower than a threshold, a question to clarify the intent;
• receiving a second input through the interactive user interface in response to output of the question through the interactive user interface, wherein the second input is associated with the first user account;
• parsing a second string of text corresponding to the second input using the trained machine learning model to revise the intent and increase the confidence level;
• and
• initiating an interaction between the first user account and a second user account based on the revised intent.

A system for intent clarification and intent-based interactivity, the system comprising:

• a memory storing instruction;
• and
• a processor, wherein execution of the instructions by the processor causes the processor to:
• receive a first input through an interactive user interface, wherein the first input is associated with a first user account;
• retrieve historical first user account information associated with the first user account from a data structure based on the first input;
• parse a first string of text corresponding to the first input using a trained machine learning model to predict an intent associated with the first user account, wherein the trained machine learning model considers the historical first user account information as context for parsing the first string of text to predict the intent, wherein the trained machine learning model includes a plurality of nodes arranged in a plurality of layers, wherein the trained machine learning model includes a plurality of connections between nodes, and wherein the plurality of connections correspond to a plurality of memory elements that store numeric weights;
• generate, based on a confidence level associated with the prediction of the intent being lower than a threshold, a question to clarify the intent;
• receive a second input through the interactive user interface in response to output of the question through the interactive user interface, wherein the second input is associated with the first user account;
• parse a second string of text corresponding to the second input using the trained machine learning model to revise the intent and increase the confidence level;
• and
• initiate an interaction between the first user account and a second user account based on the revised intent.

A non-transitory computer readable storage medium having embodied thereon a program, wherein the program is executable by a processor to perform a method of intent clarification and intent-based interactivity, the method comprising:

• receiving a first input through an interactive user interface, wherein the first input is associated with a first user account;
• retrieving historical first user account information associated with the first user account from a data structure based on the first input;
• parsing a first string of text corresponding to the first input using a trained machine learning model to predict an intent associated with the first user account, wherein the trained machine learning model considers the historical first user account information as context for parsing the first string of text to predict the intent, wherein the trained machine learning model includes a plurality of nodes arranged in a plurality of layers, wherein the trained machine learning model includes a plurality of connections between nodes, and wherein the plurality of connections correspond to a plurality of memory elements that store numeric weights;
• generating, based on a confidence level associated with the prediction of the intent being lower than a threshold, a question to clarify the intent;
• receiving a second input through the interactive user interface in response to output of the question through the interactive user interface, wherein the second input is associated with the first user account;
• parsing a second string of text corresponding to the second input using the trained machine learning model to revise the intent and increase the confidence level;
• and
• initiating an interaction between the first user account and a second user account based on the revised intent.