Intelligently identifying a user's relationship with a document

1. A data processing system comprising:

a processor; and

a memory in communication with the processor, the memory comprising executable instructions that, when executed by the processor, cause the data processing system to perform functions of:

receiving data relating to one or more activities performed by a user on a document within a given time period, the one or more activities being performed by using an application;

automatically processing the data to identify a category of user activity for the document based at least on a type of activity performed on the document;

identifying a lifecycle stage for the document based on at least the identified category of user activity; and

providing a signal for storage in association with the document, the signal including the identified lifecycle stage.

2. The data processing system of claim 1 , wherein the lifecycle stage includes at least one of creation, authoring, reviewing, reading and editing.

3. The data processing system of claim 1 , wherein the data includes at least one of a list of user activities performed on the document during the given time period, a user identifier, a document identifier, an application mode, and a time at which the given time period ended.

4. The data processing system of claim 1 , wherein the lifecycle stage is identified based on the identified category of user activity and at least one of a user category history of the document or a lifecycle stage history of the document.

5. The data processing system of claim 1 , wherein identifying the lifecycle stage for the document is done by using one or more machine-learning (ML) models.

6. The data processing system of claim 1 , wherein the executable instructions when executed by the processor, further cause the data processing system to perform functions of:

identifying a level of activity for the document based on at least one of a number of activities performed on the document during the given time period and the type of activity performed on the document,

wherein the signal for storage includes the identified level of activity.

7. The data processing system of claim 6 , wherein the lifecycle stage is identified based on the identified category of user activity and the identified level of activity.

8. The data processing system of claim 6 , wherein the level of activity includes at least one of non-active, low activity, active, very active, and extremely active.

9. The data processing system of claim 1 , wherein the executable instructions when executed by the processor, further cause the data processing system to perform functions of providing the identified lifecycle stage for display in association with the document, when information about the document is presented.

10. A method for identifying a lifecycle stage for a document comprising:

receiving data relating to one or more activities performed by a user on a document within a specific time period, the one or more activities being performed by using an application;

automatically processing the data to identify a category of user activity for the document based at least on a type of activity performed on the document;

identifying a lifecycle stage for the document based on at least the identified category of user activity;

providing a signal for storage in association with the document, the signal including the identified lifecycle stage; and

providing a signal for storage in association with the document, the signal including the identified lifecycle stage.

11. The method of claim 10 , wherein the lifecycle stage includes at least one of creation, authoring, reviewing, reading and editing.

12. The method of claim 10 , wherein the lifecycle stage is identified based on the identified category of user activity and at least one of a user category history of the document or a lifecycle stage history of the document.

13. The method of claim 10 , wherein identifying the lifecycle stage for the document is done by using one or more machine-learning (ML) models.

14. The method of claim 10 , further comprising:

identifying a level of activity for the document based on at least one of a number of activities performed on the document during the specific time period and the type of activity performed on the document,

wherein the signal for storage includes the identified level of activity.

15. The method of claim 14 , wherein the lifecycle stage is identified based on the identified category of user activity and the identified level of activity.

16. The method of claim 14 , wherein the level of activity includes at least one of non-active, low activity, active, very active, and extremely active.

17. The method of claim 10 , providing the identified lifecycle stage for display in association with the document, when information about the document is presented.

18. A non-transitory computer readable medium on which are stored instructions that when executed cause a programmable device to perform functions of:

receiving data relating to one or more activities performed by a user on a document within a given time period, the one or more activities being performed by using an application;

automatically processing the data to identify a category of user activity for the document based at least on a type of activity performed on the document;

identifying a lifecycle stage for the document based on at least the identified category of user activity; and

providing a signal for storage in association with the document, the signal including the identified lifecycle stage.

19. The non-transitory computer readable medium of claim 18 , wherein the instructions when executed cause a programmable device to further perform functions of:

identifying a level of activity for the document based on at least one of a number of activities performed on the document during the given time period and the type of activity performed on the document, and

wherein the signal for storage includes the identified level of activity.

20. The non-transitory computer readable medium of claim 18 , wherein a model for identifying the category of user activity or identifying the lifecycle stage is trained by using a training data set that includes user feedback.