Method and device for pushing information and method and device for determining default input value

1. A computer-implemented method, the computer-implemented method comprising:

retrieving, by one or more processors, historical information of an item of a user;

providing, by the one or more processors, as input the historical information to a classification model of a machine learning algorithm, wherein the classification model of the machine learning algorithm is configured to process the historical information and provides as output a projected change of one or more parameters of the item within a time period, wherein the time period is dynamically adjusted by determining statistical values for each of a plurality of time periods, during which the one or more parameters of the item change, by using the historical information and by determining the time period based on a statistical condition for an expected change as a characteristic time period of the plurality of time periods;

determining, by the one or more processors, service information for the item based on the projected change of the one or more parameters of the item within the time period by providing the historical information of the item as input for the classification model of the machine learning algorithm that was trained with labeled time periods comprising expected changes of the one or more parameters of the item;

generating, by the one or more processors, a management suggestion for the item based on the service information, the management suggestion comprising a default value for the item, a suggested item service, and a performance frequency for the suggested item service within the time period;

transmitting, by the one or more processors, the management suggestion configured to be displayed on a graphical user interface of a user device;

monitoring, by the one or more processors, current information of the item of the user; and

adjusting, by the one or more processors, the time period based on the current information of the item of the user.

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

satisfying a first condition by a frequency of the projected change of the one or more parameters of the item;

satisfying a second condition by comparing the projected change of the one or more parameters of the item to a change amount; or

satisfying a third condition by comparing the projected change of the one or more parameters of the item to a change balance.

3. The computer-implemented method of claim 1 , further comprising:

monitoring a change of the item of the user during the time period;

determining that the projected change of the one or more parameters of the item occurred; and

in response to determining that the projected change of the one or more parameters of the item occurred, transmitting the service information to the user.

4. The computer-implemented method of claim 1 , wherein the service information comprises management service information for the item.

5. The computer-implemented method of claim 1 , further comprising:

processing the historical information to determine whether the item of the user was below a threshold.

6. A non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising:

retrieving historical information of a item of a user;

providing as input the historical information to a classification model of a machine learning algorithm, wherein the classification model of the machine learning algorithm is configured to process the historical information and provides as output a projected change of one or more parameters of the item within a time period, wherein the time period is dynamically adjusted by determining statistical values for each of a plurality of time periods, during which the one or more parameters of the item change, by using the historical information and by determining the time period based on a statistical condition for an expected change as a characteristic time period of the plurality of time periods;

determining service information for the item based on the projected change of the one or more parameters of the item within the time period by providing the historical information of the item as input for the classification model of the machine learning algorithm that was trained with labeled time periods comprising expected changes of the one or more parameters of the item;

generating a management suggestion for the item based on the service information, the management suggestion comprising a default value for the item, a suggested item service, and a performance frequency for the suggested item service within the time period;

transmitting the management suggestion configured to be displayed on a graphical user interface of a user device;

monitoring current information of the item of the user; and

adjusting the time period based on the current information of the item of the user.

7. The non-transitory, computer-readable medium of claim 6 , wherein the statistical condition comprises:

satisfying a first condition by a frequency of the projected change of the one or more parameters of the item;

satisfying a second condition by comparing the projected change of the one or more parameters of the item to a change amount; or

satisfying a third condition by comparing the projected change of the one or more parameters of the item to a change balance.

8. The non-transitory, computer-readable medium of claim 6 , the operations further comprising:

monitoring a change of the item of the user during the time period;

determining that the projected change of the one or more parameters of the item occurred; and

in response to determining that the projected change of the one or more parameters of the item occurred, transmitting the service information to the user.

9. The non-transitory, computer-readable medium of claim 6 , wherein the service information comprises management service information for the item.

10. The non-transitory, computer-readable medium of claim 6 , the operations further comprising:

processing the historical information to determine whether the item of the user was below a threshold.

11. A computer-implemented system, comprising:

one or more computers; and

one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, perform one or more operations comprising:

retrieving historical information of a item of a user,

providing as input the historical information to a classification model of a machine learning algorithm, wherein the classification model of the machine learning algorithm is configured to process the historical information and provides as output a projected change of one or more parameters of the item within a time period, wherein the time period is dynamically adjusted by determining statistical values for each of a plurality of time periods, during which the one or more parameters of the item change, by using the historical information and by determining the time period based on a statistical condition for an expected change as a characteristic time period of the plurality of time periods,

determining service information for the item based on the projected change of the one or more parameters of the item within the time period by providing the historical information of the item as input for the classification model of the machine learning algorithm that was trained with labeled time periods comprising expected changes of the one or more parameters of the item,

generating a management suggestion for the item based on the service information, the management suggestion comprising a default value for the item, a suggested item service, and a performance frequency for the suggested item service within the time period,

transmitting the management suggestion configured to be displayed on a graphical user interface of a user device,

monitoring current information of the item of the user, and

adjusting the time period based on the current information of the item of the user.

12. The computer-implemented system of claim 11 ,

wherein the statistical condition comprises:

satisfying a first condition by a frequency of the projected change of the one or more parameters of the item;

satisfying a second condition by comparing the projected change of the one or more parameters of the item to a change amount; or

satisfying a third condition by comparing the projected change of the one or more parameters of the item to a change balance.

13. The computer-implemented system of claim 11 , the operations further comprising:

monitoring a change of the item of the user during the time period;

determining that the projected change of the one or more parameters of the item occurred; and

in response to determining that the projected change of the one or more parameters of the item occurred, transmitting the service information to the user.

14. The computer-implemented system of claim 11 , wherein the service information comprises management service information for the item.

15. The computer-implemented system of claim 11 , the operations further comprising:

processing the historical information to determine whether the item of the user was below a threshold.