System to associate a demographic to a user of an electronic system

1. A computerized method for associating a user of an electronic system with a demographic group by measuring behavioral dynamics in operating an input device, comprising:

accessing a first data characteristic of a user of an electronic system measured performing a first prescribed interaction with an input device of the electronic system;

accessing a probability distribution representation for a first demographic group representative of a plurality of individuals within the first demographic group performing the first prescribed interaction;

accessing a probability distribution representation for a wide population to include a plurality of demographic groups performing the first prescribed interaction;

determining a first posterior probability whether the user is a member of the first demographic group, by comparing (a) the data characteristic of the user, (b) the probability distribution representation for the first demographic group, and (c) the probability distribution representation for the wide population;

accessing a second data characteristic of a user of an electronic system performing a second prescribed interaction with an input device of the electronic system;

accessing a probability distribution representation for a first demographic group representative of a plurality of individuals within the first demographic group performing the second prescribed interaction; and

accessing a probability distribution representation for a wide population to include a plurality of demographic groups performing the second prescribed interaction;

determining a second posterior probability whether the user is a member of the first demographic group, by comparing (a) the data characteristic of the user, (b) the probability distribution representation for the first demographic group, and (c) the probability distribution representation for the wide population, with regard to the second prescribed interaction; and

associating the user with the first demographic group, when a total posterior probability, based on the first posterior probability and the second posterior probability, is above a prescribed threshold.

2. The computerized method for associating a user of an electronic system with a demographic as recited in claim 1 , wherein first data characteristic incorporates a plurality of instances of the user performing the first prescribed interaction, smoothed via kernel function.

3. The computerized method for associating a user of an electronic system with a demographic as recited in claim 1 , wherein the input device is a keyboard or an X-Y device.

4. The computerized method for associating a user of an electronic system with a demographic as recited in claim 2 , wherein the interaction is measured with regards to timing, acceleration, or velocity to perform the interaction with the input device.

5. The computerized method for associating a user of an electronic system with a demographic as recited in claim 1 , further comprising:

a first comparing, by comparing (a) the probability distribution representation for the first demographic group performing the first prescribed interaction to (b) the probability distribution representation for the wide population performing the first prescribed interaction;

determining a first weighting value associated with the first prescribed interaction based on the first comparing;

a second comparing, by comparing (a) the probability distribution representation for the first demographic group performing the second prescribed interaction to (b) the probability distribution representation for the wide population performing the second prescribed interaction;

determining a second weighting value associated with the second prescribed interaction based on the second comparing;

determining a total posterior probability by associating the first weighting value with the first posterior probability and the second weighting value is associated with the second posterior probability.

6. The computerized method for associating a user of an electronic system with a demographic as recited in claim 1 , wherein:

the probability distribution representation for the first demographic group performing the first prescribed interaction is based on a plurality of measurements of a plurality of members of the demographic group performing the first prescribed interaction, smoothed via a kernel function; and

the probability distribution representation for the first demographic group performing the first prescribed interaction further accounts for parameters for time of day and type of application for the first prescribed interaction.

7. The computerized method for associating a user of an electronic system with a demographic as recited in claim 1 , wherein the probability distribution representation for the demographic group is configured to capture time intervals for performing n-graph keyboard dynamics in a continuous manner while users interact with the system.

8. The computerized method for associating a user of an electronic system with a demographic as recited in claim 1 , wherein the probability distribution representation for the wide population is scalable to represent users of a very large-scale electronic system.

9. A computerized method for associating a user of an electronic system with a demographic group by measuring behavioral dynamics in operating an input device, the method comprising:

capturing input behavioral data for a plurality of users to include a prescribed user, the input behavioral data related to measured interactions with input devices to include a keyboard and an X-Y device, in which the measured interactions include a first interaction and a second interaction;

maintaining a plurality of probability distribution representations for a wide population of users based on the captured data inclusive of the first interaction and the second interaction, in which each wide-population probability distribution representation for a wide population is associated to a single prescribed interaction;

maintaining a plurality of probability distribution representations for a plurality of demographic groups based on the captured data inclusive of the first interaction and the second interaction, in which each demographic probability distribution representation is associated to a single prescribed interaction for single demographic group;

determining a first probability whether the prescribed user is a member of a first demographic group, by comparing (a) input behavioral data associated with the current user performing the first interaction, (b) the probability distribution representation for the first demographic group performing the first interaction, and (c) the probability distribution representation for the wide population performing the first interaction;

determining a second probability whether the prescribed user is a member of a first demographic group, by comparing (a) input behavioral data associated with the current user performing the second interaction, (b) the probability distribution representation for the first demographic group performing the second interaction, and (c) the probability distribution representation for the wide population performing the second interaction; and

associating the prescribed user with the first demographic group when the total probability, based on the first probability and the second probability, is above a prescribed threshold.

10. The computerized method for associating a user of an electronic system with a demographic as recited in claim 9 , wherein the probability distribution representations for the wide population are scalable to represent users of a very large-scale electronic system.

11. The computerized method for associating a user of an electronic system with a demographic as recited in claim 9 , wherein the probability distribution representation for the first demographic group performing the first interaction further accounts for parameters for time of day and type of application.

12. The computerized method for associating a user of an electronic system with a demographic as recited in claim 9 , wherein the probability distribution representation for the first demographic group is configured to capture time intervals for performing n-graph keyboard dynamics in a continuous manner while users interact with the system.

13. A computerized method for associating a user of an electronic system with a demographic group by measuring behavioral dynamics in operating an input device, the method comprising:

capturing input behavioral data for a plurality of users to include a current user, the input behavioral data related to measured interactions with input devices to include a keyboard and an X-Y device, in which the measured interactions include a first interaction and a second interaction distinct from the first interaction;

maintaining a plurality of probability distribution representations for a wide population of users based on the captured data, in which each wide-population probability distribution representation for a wide population is associated to a single prescribed interaction to include an n-graph keystroke dynamic;

maintaining a plurality of probability distribution representations for a plurality of demographic groups based on the captured data, in which each demographic probability distribution representation is associated to a single prescribed interaction to include an n-graph keystroke dynamic for single demographic group;

determining a first probability whether the user is a member of the first demographic group, by comparing (a) input behavioral data associated with the current user performing the first interaction, (b) the probability distribution representation for the first demographic group performing the first interaction, and (c) the probability distribution representation for the wide population performing the first interaction;

determining a second probability whether the user is a member of the first demographic group, by comparing (a) input behavioral data associated with the current user performing the second interaction, (b) the probability distribution representation for the first demographic group performing the second interaction, and (c) the probability distribution representation for the wide population performing the second interaction;

determining a total probability based on the first probability and the second probability; and

associating the current user with the first demographic group when the total probability is above a prescribed threshold.

14. The computerized method for associating a user of an electronic system with a demographic as recited in claim 13 , wherein the probability distribution representation for the first demographic group performing the first interaction further accounts for parameters for time of day and type of application.

15. The computerized method for associating a user of an electronic system with a demographic as recited in claim 13 , wherein the probability distribution representation for the first demographic group is configured to capture time intervals for performing n-graph keyboard dynamics in a continuous manner while users interact with the system.

16. A computerized method for associating a user of an electronic system with a demographic group by measuring behavioral dynamics in operating an input device, the method comprising:

capturing input behavioral data for a plurality of users to include a current user, the input behavioral data related to measured interactions with input devices to include a keyboard and an X-Y device, in which the measured interactions include a first interaction and a second interaction distinct from the first interaction;

maintaining a plurality of probability distribution representations for a wide population of users based on the captured data, in which each wide-population probability distribution representation for a wide population is associated to a single prescribed interaction to include an n-graph keystroke dynamic;

maintaining a plurality of probability distribution representations for a plurality of demographic groups based on the captured data, in which each demographic probability distribution representation is associated to a single prescribed interaction to include an n-graph keystroke dynamic for single demographic group;

a first comparing, by comparing (a) the probability distribution representation for a first demographic group performing the first interaction to (b) the probability distribution representation for the wide population performing the first interaction;

determining a first weighting value associated with the first interaction based on the first comparing;

a second comparing, by comparing (a) the probability distribution representation for the first demographic group performing the second interaction to (b) the probability distribution representation for the wide population performing the second interaction;

determining a second weighting value associated with the second interaction based on the second comparing;

determining a first probability whether the user is a member of the first demographic group, by comparing (a) input behavioral data associated with the current user performing the first interaction, (b) the probability distribution representation for the first demographic group performing the first interaction, and (c) the probability distribution representation for the wide population performing the first interaction;

determining a second probability whether the user is a member of the first demographic group, by comparing (a) input behavioral data associated with the current user performing the second interaction, (b) the probability distribution representation for the first demographic group performing the second interaction, and (c) the probability distribution representation for the wide population performing the second interaction;

determining a total probability by associating the first weighting value with the first probability and the second weighting value is associated with the second probability; and

associating the current user with the first demographic group when the total probability is above a prescribed threshold.

17. The computerized method for associating a user of an electronic system with a demographic as recited in claim 16 , wherein the probability distribution representation for the first demographic group performing the first interaction further accounts for parameters for time of day and type of application.

18. The computerized method for associating a user of an electronic system with a demographic as recited in claim 16 , wherein the probability distribution representation for the first demographic group is configured to capture time intervals for performing n-graph keyboard dynamics in a continuous manner while users interact with the system.