Parameterized method, device, and user interface for enabling filtering

1 . A computer-implemented method for processing an information screen to enable filtering of another information screen, comprising:

identifying a user interface (UI) element code for the information screen based at least in part on a parameter data structure, wherein the UI element code is configured to perform a first action comprising requesting the other information screen;

requesting, from an artificial intelligence engine, a set of filter responses of a plurality of filter responses based at least in part on the parameter data structure, wherein the artificial intelligence engine selects the set of filter responses based on calculating a respective score for how each set of filter responses of the plurality of filter responses performs over a period of time involving a threshold number of users;

receiving the set of filter responses;

generating a variation of the information screen with a set of UI elements based at least in part on the UI element code and the set of filter responses, wherein each UI element in the set of UI elements is configured to perform the first action performed by the UI element code and a second action comprising filtering the other information screen using a filter response in the set of filter responses; and

outputting the variation of the information screen with the set of UI elements.

2 . The computer-implemented method of claim 1 , wherein the requesting comprises:

requesting the set of filter responses from the artificial intelligence engine based on at least one of a category, a user profile, or a context variable, wherein the context variable is based on a previous user interaction or a characteristic of an electronic device.

3 . The computer-implemented method of claim 1 , wherein the generating comprises:

generating the set of UI elements in place of the UI element code based on an order of the set of filter responses.

4 . The computer-implemented method of claim 1 , wherein the set of filter responses is generated using the artificial intelligence engine based on at least one of a periodic schedule, a category associated with the parameter data structure, a user profile, or a context variable, wherein the context variable is based on a previous user interaction or a characteristic of an electronic device.

5 . The computer-implemented method of claim 1 , wherein the artificial intelligence engine orders a filter response in the set of filter responses based on an ordinal number or a weight associated with the filter response.

6 . The computer-implemented method of claim 1 , wherein the artificial intelligence engine selects a first filter response from a first set of filter responses based on a weight or a category associated with the first filter response, selects a second filter response from a second set of filter responses based on a weight or a category associated with the second filter response, and aggregates the first filter response and the second filter response into the set of filter responses.

7 . The computer-implemented method of claim 6 , wherein the artificial intelligence engine selects the first set of filter responses based on a user profile being associated with the first set of filter responses, and selects the second set of filter responses based on the user profile being associated with the second set of filter responses.

8 . A system, comprising:

one or more memories; and

at least one processor coupled to at least one of the memories and configured to perform operations comprising:

identifying a user interface (UI) element code for an information screen based at least in part on a parameter data structure, wherein the UI element code is configured to perform a first action comprising requesting another information screen;

requesting, from an artificial intelligence engine, a set of filter responses of a plurality of filter responses based at least in part on the parameter data structure, wherein the artificial intelligence engine selects the set of filter responses based on calculating a respective score for how each set of filter responses of the plurality of filter responses performs over a period of time involving a threshold number of users;

receiving the set of filter responses;

generating a variation of the information screen with a set of UI elements based at least in part on the UI element code and the set of filter responses, wherein each UI element in the set of UI elements is configured to perform the first action performed by the UI element code and a second action comprising filtering the other information screen using a filter response in the set of filter responses; and

outputting the variation of the information screen with the set of UI elements.

9 . The system of claim 8 , wherein the requesting the set of filter responses comprises:

requesting the set of filter responses from the artificial intelligence engine based on at least one of a category, a user profile, or a context variable, wherein the context variable is based on a previous user interaction or a characteristic of the system.

10 . The system of claim 8 , wherein the generating the set of UI elements comprise:

generate the set of UI elements in place of the UI element code based on an order of the set of filter responses.

11 . The system of claim 8 , wherein the set of filter responses is generated using the artificial intelligence engine based on at least one of a periodic schedule, a category associated with the parameter data structure, a user profile, or a context variable, wherein the context variable is based on a previous user interaction or a characteristic of the system.

12 . The system of claim 8 , wherein the artificial intelligence engine orders a filter response in the set of filter responses based on an ordinal number or a weight associated with the filter response.

13 . The system of claim 8 , wherein the artificial intelligence engine selects a first filter response from a first set of filter responses based on a weight or a category associated with the first filter response, selects a second filter response from a second set of filter responses based on a weight or a category associated with the second filter response, and aggregates the first filter response and the second filter response into the set of filter responses.

14 . The system of claim 13 , wherein the artificial intelligence engine selects the first set of filter responses based on a user profile being associated with the first set of filter responses, and selects the second set of filter responses based on the user profile being associated with the second set of filter responses.

15 . A non-transitory computer-readable medium having instructions stored thereon that, when executed by at least one computing device, causes the at least one computing device to perform operations comprising:

identifying a user interface (UI) element code for an information screen based at least in part on a parameter data structure, wherein the UI element code is configured to perform a first action comprising requesting another information screen;

requesting, from an artificial intelligence engine, a set of filter responses of a plurality of filter responses based at least in part on the parameter data structure, wherein the artificial intelligence engine selects the set of filter responses based on calculating a respective score for how each set of filter responses of the plurality of filter responses performs over a period of time involving a threshold number of users;

receiving the set of filter responses;

generating a variation of the information screen with a set of UI elements based at least in part on the UI element code and the set of filter responses, wherein each UI element in the set of UI elements is configured to perform the first action performed by the UI element code and a second action comprising filtering the other information screen using a filter response in the set of filter responses; and

outputting the variation of the information screen with the set of UI elements.

16 . The non-transitory computer-readable medium of claim 15 , wherein the requesting comprises:

requesting the set of filter responses from the artificial intelligence engine based on at least one of a category, a user profile, or a context variable, wherein the context variable is based on a previous user interaction or a characteristic of the at least one computing device.

17 . The non-transitory computer-readable medium of claim 15 , wherein the generating comprises:

generating the set of UI elements in place of the UI element code based on an order of the set of filter responses.

18 . The non-transitory computer-readable medium of claim 15 , wherein the set of filter responses is generated using the artificial intelligence engine based on at least one of a periodic schedule, a category associated with the parameter data structure, a user profile, or a context variable, wherein the context variable is based on a previous user interaction or a characteristic of the at least one computing device.

19 . The non-transitory computer-readable medium of claim 15 , wherein the artificial intelligence engine orders a filter response in the set of filter responses based on an ordinal number or a weight associated with the filter response.

20 . The non-transitory computer-readable medium of claim 15 , wherein the artificial intelligence engine selects a first filter response from a first set of filter responses based on a weight or a category associated with the first filter response, selects a second filter response from a second set of filter responses based on a weight or a category associated with the second filter response, and aggregates the first filter response and the second filter response into the set of filter responses.