Estimating a composition of a population
View Patent ↗A method performed by one or more processing devices includes receiving data indicative of amounts of users in population segments that access a resource; applying an expectation-maximization algorithm to the data received; generating, based on applying, estimates of weights indicative of an accuracy of the amounts of users; wherein the expectation-maximization algorithm is applied and the estimates are generated until the estimates reach an asymptotic approximation of the weights; adjusting the amounts of the users in accordance with the estimates of the weights; and generating, based on the amounts of the users adjusted, an estimate of a composition of a population of users that access the resource.
1. A method performed by one or more processing devices, comprising:
receiving data indicative of amounts of users in population segments that access a resource;
applying an expectation-maximization algorithm to the data received;
generating, based on applying, estimates of weights indicative of an accuracy of the amounts of users;
wherein the expectation-maximization algorithm is applied and the estimates are generated until the estimates reach an asymptotic approximation of the weights;
adjusting the amounts of the users in accordance with the estimates of the weights;
counting a number of users that access the resource; and
generating, based on the amounts of the users adjusted and the number of users counted, an estimate of a composition of a population of users that access the resource.
2. The method of claim 1 , wherein receiving the data indicative of the amounts of users comprises:
receiving population composition data indicative of the amounts of users in the population segments; and
wherein the estimate of the composition of the population comprises weighted population composition data.
3. The method of claim 1 , wherein the estimate of the composition of the population comprises:
estimates of numbers of users in the population segments.
4. The method of claim 1 , wherein the amounts of the users adjusted has increased accuracy relative to an accuracy of the amounts of users in the data received.
5. The method of claim 1 , where the data received is received from a single biased data source.
6. One or more machine-readable hardware storage devices storing instructions that are executable by one or more processing devices to perform operations comprising:
receiving data indicative of amounts of users in population segments that access a resource;
applying an expectation-maximization algorithm to the data received;
generating, based on applying, estimates of weights indicative of an accuracy of the amounts of users;
wherein the expectation-maximization algorithm is applied and the estimates are generated until the estimates reach an asymptotic approximation of the weights;
adjusting the amounts of the users in accordance with the estimates of the weights;
counting a number of users that access the resource; and
generating, based on the amounts of the users adjusted and the number of users counted, an estimate of a composition of a population of users that access the resource.
7. The one or more machine-readable hardware storage devices of claim 6 , wherein receiving the data indicative of the amounts of users comprises:
receiving population composition data indicative of the amounts of users in the population segments; and
wherein the estimate of the composition of the population comprises weighted population composition data.
8. The one or more machine-readable hardware storage devices of claim 6 , wherein the estimate of the composition of the population comprises:
estimates of numbers of users in the population segments.
9. The one or more machine-readable hardware storage devices of claim 6 , wherein the amounts of the users adjusted has increased accuracy relative to an accuracy of the amounts of users in the data received.
10. The one or more machine-readable hardware storage devices of claim 6 , where the data received is received from a single biased data source.
11. An electronic system comprising:
one or more processing devices; and
one or more machine-readable hardware storage devices storing instructions that are executable by the one or more processing devices to perform operations comprising:
receiving data indicative of amounts of users in population segments that access a resource;
applying an expectation-maximization algorithm to the data received;
generating, based on applying, estimates of weights indicative of an accuracy of the amounts of users;
wherein the expectation-maximization algorithm is applied and the estimates are generated until the estimates reach an asymptotic approximation of the weights;
adjusting the amounts of the users in accordance with the estimates of the weights;
counting a number of users that access the resource; and
generating, based on the amounts of the users adjusted and the number of users counted, an estimate of a composition of a population of users that access the resource.
12. The electronic system of claim 11 , wherein receiving the data indicative of the amounts of users comprises:
receiving population composition data indicative of the amounts of users in the population segments; and
wherein the estimate of the composition of the population comprises weighted population composition data.
13. The electronic system of claim 11 , wherein the estimate of the composition of the population comprises:
estimates of numbers of users in the population segments.
14. The electronic system of claim 11 , wherein the amounts of the users adjusted has increased accuracy relative to an accuracy of the amounts of users in the data received.
15. The electronic system of claim 11 , where the data received is received from a single biased data source.