Database access system using machine learning-based relationship association
A system includes a processor configured to perform operations. The operations include receiving responses to at least first and second questions from a user device over a network; and using a machine-learning algorithm to determine a relationship between the first and second questions based on the received responses; assign to the first and second questions, a relationship value between 0 and 1 based on the determined relationship, wherein the relationship value represents a likelihood the response to the first question is associated with the response to the second question; designate the first or second question as a critical question when a determined relationship value is greater than 0.5; and determine a need of the user based on the response of the user to the critical question. Operations further include generating and providing to the use device a list of service providers based on the determined need of the user.
1 . A system for using machine learning-based relationship association to assess a user need, the system comprising:
at least one processor; and
a storage medium storing instructions that, when executed, configure the at least one processor to perform operations comprising:
receiving from a user device one of an electronic service request or registration request;
transmitting to the user device for display on a user interface, over a communication network, a questionnaire with at least a first and second question in response to the request of the user;
receiving responses to the first and second questions from the user device over the network;
generating a relationship map between the first and second questions based on the received responses;
determining, using a machine-learning algorithm, a relationship between the first and second questions based on the received responses;
assigning to the first and second questions, using the machine-learning algorithm, a relationship value between 0 and 1 based on the determined relationship, wherein the relationship value represents a likelihood the response to the first question is associated with the response to the second question;
determining, using the machine-learning algorithm, one of the first or second question has a relationship value greater than 0.5;
designating, using the machine-learning algorithm, the first or second question as a critical question when the relationship value is greater than 0.5;
determining, using the machine-learning algorithm, a need of the user based on the response of the user to the critical question;
accessing a database to generate a list of service providers based on the determined need of the user; and
providing the list of service providers to the user device for display on the user interface.
2 . The system of claim 1 , wherein the critical question is a critical behavioral question.
3 . The system of claim 2 , wherein the operations further comprise:
determining a behavioral need associated with the response of the user to the critical behavioral question.
4 . The system of claim 2 , wherein the operations further comprise:
generating a list of one or more critical behavioral questions,
transmitting the generated list of critical behavioral questions to at least one service provider for treating the behavioral need.
5 . The system of claim 1 , wherein the operations further comprise:
storing the number of critical responses received from the user device in the database.
6 . The system of claim 1 , wherein the operations further comprise:
determining a location of the user device based on a signal transmitted from the user device.
7 . The system of claim 6 , wherein the operations further comprise using the determined location to generate the list of service providers.
8 . The system of claim 1 , wherein the operations further comprise:
determining, using the machine-learning algorithm, based on the response of the user to the critical question, a likelihood that the user will benefit from receiving services of a service provider from the list of service providers.
9 . The system of claim 1 , wherein the operations further include training the machine learning algorithm using the user responses.
10 . The system of claim 1 , wherein the critical question has a relationship value greater than 0.7.
11 . The system of claim 1 , wherein the operations further comprise using a response to the questionnaire to automatically customize another question of the questionnaire.
12 . The system of claim 1 , wherein:
the determining the need of the user based on the response of the user to the critical question is performed based on the designation of the critical question.
13 . The system of claim 1 , further comprising:
transmitting the critical question upon the designation as a critical question, or
storing the critical question upon the designation as a critical question.
14 . The system of claim 1 , wherein the relationship map indicates how a response to the first question is predictive of a response to the second question.
15 . The system of claim 14 , wherein the relationship map further indicates how a response to the first question is predictive of a response to a third question and how a response to the second question is predictive of a response to the third question.
16 . The system of claim 1 , wherein determining the relationship between the first and second questions is based on the generated relationship map.
17 . The system of claim 1 , wherein, upon designating one or more questions as critical questions, the system determines the user's need based on the responses to the critical questions without presenting or requiring responses to additional questions of the questionnaire.