Training an artificial intelligence engine for most appropriate products

Abstract

A system for guiding interactions with a user device requests a response from a plurality of users, stores the response as response data forming a subset of a personal data set of each of the responding users, and generates a predictive model during training of a machine learning program utilizing at least one neural network with a training data set including the personal data set of each of the plurality of users. The predictive model predicts a probability of a first one of the users associated with the user device interacting with a first product and/or service by correlating a personal data set of the first one of the users to the personal data set of at least a second one of the users and sends a communication relating to the first product and/or service to the user device when the predicted probability meets or exceeds a threshold value.

1 . A system for guiding interactions with a user device, the system comprising:
 a computer with one or more processor and memory, wherein the computer executes computer-readable instructions to guide the interactions with the user device, the computer managed by a business entity; and   a network connection operatively connecting the user device to the computer;   wherein, upon execution of the computer-readable instructions, the computer performs steps comprising:
 requesting a response from a plurality of users, wherein each of the users has an account with the business entity, wherein the account of each of the users is accessible via a software application and/or a website managed by the computer of the business entity, wherein the account of each of the users is associated with an account setting, wherein the account setting is associated with a manner in which the computer interacts with a respective user device of each of the respective users via the software application and/or the website managed by the computer of the business entity, wherein the response of each of the responding users relates to a preference of each of the responding users regarding a selection of the account setting for determining the manner in which the computer interacts with the respective user device of each of the respective users via the software application and/or the website managed by the computer of the business entity; 
 storing the response of each of the responding users as response data, the response data forming a subset of a personal data set of each of the responding users; 
 generating a predictive model during training of a machine learning program utilizing at least one neural network, a training data set utilized during the training of the machine learning program comprising the personal data set of each of the plurality of users; 
 predicting, by the predictive model, a probability of a first one of the users associated with the user device indicating a preference regarding a selection of the account setting, wherein the first one of the users does not correspond to one of the responding users, the predicting of the probability including the predictive model correlating a personal data set of the first one of the users to the personal data set of at least a second one of the users corresponding to one of the responding users; and 
 automatically selecting the account setting of the first one of the users to correspond to the predicted preference of the first one of the users regarding the selection of the account setting when the predicted probability meets or exceeds a threshold value, the automatic selecting of the account setting corresponding to an automatic reconfiguring of the computer to result in a change in one or more of:
 a form, a frequency, or a content of communications from the computer that are accessible to the first one of the users during execution of the software application and/or the website managed by the computer of the business entity on the user device, 
 a condition triggering the computer to communicate with the first one of the users during execution of the software application and/or the website managed by the computer of the business entity on the user device, and/or 
 a configuration of an interface of the software application and/or the website managed by the computer during execution thereof on the user device. 
 
   
     
     
         2 . The system of  claim 1 , wherein the response is requested when each of the plurality of users is enrolling or participating in a contest. 
     
     
         3 . (canceled) 
     
     
         4 . (canceled) 
     
     
         5 . (canceled) 
     
     
         6 . (canceled) 
     
     
         7 . The system of  claim 1 , wherein the response is requested when each of the plurality of users is navigating the software application and/or the website when executed on a corresponding user device. 
     
     
         8 . The system of  claim 1 , wherein the training of the machine learning program includes unsupervised learning wherein each of the entries of the training data set is unlabeled. 
     
     
         9 . The system of  claim 1 , wherein the machine learning program is configured to perform cluster analysis with respect to the training data set during the training of the predictive model. 
     
     
         10 . The system of  claim 1 , wherein the at least one neural network generates a self-organizing map. 
     
     
         11 . The system of  claim 1 , wherein the training of the machine learning program includes semi-supervised learning, wherein during the semi-supervised learning the training data set further includes data relating to whether the first one of the users changed the selection of the account setting following the automatic selection of the account setting corresponding to the predicted preference of the first one of the users. 
     
     
         12 . The system of  claim 1 , wherein the training of the machine learning program includes supervised learning with each of the entries of the training data set being labeled. 
     
     
         13 . (canceled) 
     
     
         14 . (canceled) 
     
     
         15 . (canceled) 
     
     
         16 . The system of  claim 1 , wherein the personal data set of each of the users includes demographic data. 
     
     
         17 . The system of  claim 1 , wherein the personal data set of each of the users includes a transaction history of the corresponding user. 
     
     
         18 . A method of interacting with a user device comprising the steps of:
 requesting a response from a plurality of users, wherein each of the users has an account with a business entity, wherein the account of each of the users is accessible via a software application and/or a website managed by a computer of the business entity, wherein the account of each of the users is associated with an account setting, wherein the account setting is associated with a manner in which the computer interacts with a respective user device of each of the respective users via the software application and/or the website managed by the computer of the business entity, wherein the response of each of the responding users relates to a preference of each of the responding users regarding a selection of the account setting for determining the manner in which the computer interacts with the respective user device of each of the respective users via the software application and/or the website managed by the computer of the business entity;   storing the response of each of the responding users as response data, the response data forming a subset of a personal data set of each of the responding users;   generating a predictive model during training of a machine learning program utilizing at least one neural network, a training data set utilized during the training of the machine learning program comprising the personal data set of each of the plurality of users;   predicting, by the predictive model, a probability of a first one of the users associated with the user device indicating a preference regarding a selection of the account setting, wherein the first one of the users does not correspond to one of the responding users, the predicting of the probability including the predictive model correlating a personal data set of the first one of the users to the personal data set of at least a second one of the users corresponding to one of the responding users; and   automatically selecting the account setting of the first one of the users to correspond to the predicted preference of the first one of the users regarding the selection of the account setting when the predicted probability meets or exceeds a threshold value, the automatic selecting of the account setting corresponding to an automatic reconfiguring of the computer to result in a change in one or more of:
 a form, a frequency, or a content of communications from the computer that are accessible to the first one of the users during execution of the software application and/or the website managed by the computer of the business entity on the user device, 
 a condition triggering the computer to communicate with the first one of the users during execution of the software application and/or the website managed by the computer of the business entity on the user device, and/or 
 a configuration of an interface of the software application and/or the website managed by the computer during execution thereof on the user device. 
   
     
     
         19 . The method of  claim 18 , wherein the response is requested when each of the plurality of users is enrolling or participating in a contest. 
     
     
         20 . The method of  claim 18 , wherein the response is requested when each of the plurality of users is navigating the software application and/or the website when executed on a corresponding user device.