User experience/user interface based on interaction history

1. A method comprising:

by a computing device, accessing a base user experience (UX) of a social-networking system comprising a user interface (UI) corresponding to one or more features of the social-networking system;

by the computing device, computationally determining one or more user categories based at least in part on information associated with previous interactions by a plurality of users with the social-networking system;

by the computing device, classifying a particular user into one or more of the user categories based at least in part on the interactions of the particular user with the social-networking system, wherein the classification comprises applying a machine-learning algorithm to the interactions of the particular user, and wherein the machine-learning algorithm is trained using the previous interactions by the plurality of users;

by the computing device, determining, relative to the base UX, one or more modifications comprising an addition of one or more graphical elements of the UI for display to the particular user, one or more of the graphical elements comprising a guided tour illustrating one or more of the features of the UI, the modifications being configured to personalize the UI individually to the particular user based at least in part on the computational determination of one or more of the user categories applicable to the particular user;

by the computing device, assigning a value to a particular functionality based at least in part on an objective of a computing system comprising the computing device;

by the computing device, selecting one or more of the graphical elements corresponding to the particular functionality with a highest value relative to the objective;

by the computing device, applying the modifications to the UI; and

by the computing device, providing the UI as modified for display to the particular user.

2. The method of claim 1 , wherein the computational determination is further based at least in part on information of a client device associated with the particular user used to interact with the social-networking system.

3. The method of claim 1 , wherein the user categories are further based on information associated with the plurality of users comprising a location, age, affinities, or number of friends.

4. The method of claim 3 , wherein the information associated with the plurality of users is stored on a social graph of a social-networking system, the social graph comprising a plurality of nodes and edges connecting the nodes, at least one node in the social graph corresponding to the particular user.

5. The method of claim 1 , further comprising accessing a log storing the interactions of the plurality of users with the social-networking system.

6. One or more computer-readable non-transitory storage media embodying software configured when executed to:

access a base user experience (UX) of a social-networking system comprising a user interface (UI) corresponding to one or more features of the social-networking system;

computationally determine one or more user categories based at least in part on information associated with previous interactions by a plurality of users with the social-networking system;

classify a particular user into one or more of the user categories based at least in part on the interactions of the particular user with the social-networking system, wherein the classification comprises applying a machine-learning algorithm to the interactions of the particular user, and wherein the machine-learning algorithm is trained using the previous interactions by the plurality of users;

determine, relative to the base UX, one or more modifications comprising an addition of one or more graphical elements of the UI for display to the particular user, one or more of the graphical elements comprising a guided tour illustrating one or more of the features of the UI, the modifications being configured to personalize the UI individually to the particular user based at least in part on the computational determination of one or more of the user categories applicable to the particular user;

assign a value to a particular functionality based at least in part on an objective of a computing system;

select one or more of the graphical elements corresponding to the particular functionality with a highest value relative to the objective;

apply the modifications to the UI; and

provide the UI as modified for display to the particular user.

7. The media of claim 6 , wherein the computational determination is further based at least in part on information of a client device associated with the particular user used to interact with the social-networking system.

8. The media of claim 6 , wherein the user categories are further based on information associated with the plurality of users comprising a location, age, affinities, or number of friends.

9. The media of claim 8 , wherein the information associated with the plurality of users is stored on a social graph of a social-networking system, the social graph comprising a plurality of nodes and edges connecting the nodes, at least one node in the social graph corresponding to the particular user.

10. The media of claim 6 , wherein the software is further configured to access a log storing the interactions of the plurality of users with the social-networking system.

11. A device comprising:

a processor; and

one or more computer-readable non-transitory storage media coupled to the processor and embodying software that:

access a base user experience (UX) of a social-networking system comprising a user interface (UI) corresponding to one or more features of the social-networking system;

computationally determine one or more user categories based at least in part on information associated with previous interactions by a plurality of users with the social-networking system;

classify a particular user into one or more of the user categories based at least in part on the interactions of the particular user with the social-networking system, wherein the classification comprises applying a machine-learning algorithm to the interactions of the particular user, and wherein the machine-learning algorithm is trained using the previous interactions by the plurality of users;

determine, relative to the base UX, one or more modifications comprising an addition of one or more graphical elements of the UI for display to the particular user, one or more of the graphical elements comprising a guided tour illustrating one or more of the features of the UI, the modifications being configured to personalize the UI individually to the particular user based at least in part on the computational determination of one or more of the user categories applicable to the particular user;

assign a value to a particular functionality based at least in part on an objective of a computing system;

select one or more of the graphical elements corresponding to the particular functionality with a highest value relative to the objective;

apply the modifications to the UI; and

provide the UI as modified for display to the particular user.

12. The device of claim 11 , wherein the computational determination is further based at least in part on information of a client device associated with the particular user used to interact with the social-networking system.

13. The device of claim 11 , wherein the user categories are further based on information associated with the plurality of users comprising a location, age, affinities, or number of friends.

14. The device of claim 13 , wherein the information associated with the plurality of users is stored on a social graph of a social-networking system, the social graph comprising a plurality of nodes and edges connecting the nodes, at least one node in the social graph corresponding to the particular user.

15. The device of claim 11 , wherein the software is further configured to access a log storing the interactions of the plurality of users with the social-networking system.