| CPC G06Q 30/015 (2023.01) | 20 Claims |
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1. A system configured to generate response records for individual users based on user responses to prompts, wherein the response records are structured for refining machine learning models to generate customized outputs, the system comprising: one or more physical processors configured by machine-readable instructions to:
provide prompts to individual users, wherein the prompts are presented on one or more user interfaces of client computing platforms associated with individual ones of the users, such that a first prompt is provided to a first user via a first client computing platform associated with the first user;
receive user input from the individual ones of the users, wherein user input from the individual ones of the users indicates responses to the provided prompts, such that first user input from the first user indicates a first response to the first prompt;
determine, based on the received user input from the individual ones of the users, response information for individual ones of the responses to the prompts, wherein response information for an individual response describes one or more of the content of the individual response and/or the context of the individual response, such that response information is determined for the first response;
aggregate the individual responses and corresponding response information to generate response records for the individual ones of the users, wherein an individual response record is associated with an individual user, wherein the response records for individual ones of the users are structured for use within an application marketplace that facilitates use of individual applications by the individual ones of the users, wherein the individual applications utilize one or more machine learning models to perform application functions, and wherein the one or more machine learning models are capable of being refined based on response records for the individual ones of the users to customized outputs generated by the individual machine learning models for the individual ones of the users, such that a first response record for the first user is aggregated based on the first response and/or response information for the first response;
store the response records for the individual ones of the users, such that the first response record for the first user is stored;
receive user input from the individual ones of the users indicating selection of one or more applications, such that second user input from the first user indicates selection of a first application, the first application utilizing a first machine learning model to perform application functions;
refine, based on the stored response records for the individual ones of the users, one or more underlying machine learning models that perform application functions for the one or more selected applications, such that the first machine learning model is refined based on the first response record for the first user; and
utilize the one or more refined underlying machine learning models in the performance of application functions of the one or more selected applications for the individual ones of the users, such that the first refined machine learning model is used in the performance of application functions of the first application for the first user.
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