Systems and Methods for Automating Benchmark Generation using Neural Networks for Image or Video Selection
US-2022198779-A1 · Jun 23, 2022 · US
US11687967B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11687967-B2 |
| Application number | US-202217947928-A |
| Country | US |
| Kind code | B2 |
| Filing date | Sep 19, 2022 |
| Priority date | Jun 30, 2020 |
| Publication date | Jun 27, 2023 |
| Grant date | Jun 27, 2023 |
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A disclosed example includes at least one memory, programmable circuitry, and instructions to cause the programmable circuitry to increment a first value corresponding to a first position in a vector based on a first bit value representation, the first bit value representation corresponding to a first audience member identifier; increment a second value corresponding to a second position in the vector based on a second bit value representation, the second bit value representation corresponding to a second audience member identifier; estimate the second frequency moment of the media impression data using the vector; determine the variance of the second frequency moment; and based on the second frequency moment, schedule a query of the media impression data to be processed by a computer at a future time.
Opening claim text (preview).
The invention claimed is: 1. A system to determine a variance of a second frequency moment of media impression data, the system comprising: at least one memory; programmable circuitry; and instructions to cause the programmable circuitry to: increment a first value corresponding to a first position in a vector based on a first bit value representation, the first bit value representation corresponding to a first audience member identifier; increment a second value corresponding to a second position in the vector based on a second bit value representation, the second bit value representation corresponding to a second audience member identifier; estimate the second frequency moment of the media impression data using the vector; determine the variance of the second frequency moment; and based on the second frequency moment, schedule a query of the media impression data to be processed by a computer at a future time. 2. The system of claim 1 , wherein the programmable circuitry is to determine the variance of the second frequency moment by: determining a first result by squaring the second frequency moment; doubling the first result; determining a second result by subtracting one from a number of positions in the vector; and determining a ratio of the first result and the second result. 3. The system of claim 2 , wherein the number of positions in the vector is based on a target precision threshold. 4. The system of claim 3 , wherein the programmable circuitry is to determine whether to update the target precision threshold after determining whether the computer can complete the query of the media impression data based on a processing constraint. 5. The system of claim 4 , wherein, based on a request for a more accurate second frequency moment, the programmable circuitry is to determine not to update the target precision threshold. 6. The system of claim 4 , wherein the processing constraint includes at least one of a scheduling constraint, available memory utilization, or an available processing resource. 7. The system of claim 1 , wherein the programmable circuitry is to obtain the media impression data from an audience metrics database, the media impression data corresponding to an audience member total for a media item. 8. A non-transitory computer readable medium comprising computer readable instructions which, when executed, cause processor circuitry to at least: increment, based on a first bit value representation, a first value corresponding to a first position in a vector, the first bit value representation corresponding to a first audience member; increment, based on a second bit value representation, a second value corresponding to a second position in the vector, the second bit value representation corresponding to a second audience member; estimate a second frequency moment of media impression data using the vector; determine a variance of the second frequency moment; and based on the second frequency moment, schedule a date and time for a computer to complete a query request of the media impression data. 9. The non-transitory computer readable medium of claim 8 , wherein the instructions are to cause the processor circuitry to determine the variance of the second frequency moment by: determining a first result by squaring the second frequency moment; doubling the first result; determining a second result by subtracting one from a number of positions in the vector; and determining a ratio of the first result and the second result. 10. The non-transitory computer readable medium of claim 9 , wherein the number of positions in the vector is based on a target precision threshold. 11. The non-transitory computer readable medium of claim 10 , wherein the instructions are to cause the processor circuitry to determine whether to update the target precision threshold after determining whether the computer can complete the query request of the media impression data based on a processing constraint. 12. The non-transitory computer readable medium of claim 11 , wherein, based on a request for a more accurate second frequency moment, the instructions are to cause the processor circuitry to determine not to update the target precision threshold. 13. The non-transitory computer readable medium of claim 11 , wherein the processing constraint includes at least one of a scheduling constraint, available memory utilization, or an available processing resource. 14. The non-transitory computer readable medium of claim 8 , wherein the instructions are to cause the processor circuitry to obtain the media impression data from an audience metrics database, the media impression data corresponding to an audience member total for a media item. 15. A method comprising: incrementing, by executing an instruction with a processor, a first value corresponding to a first position in a vector, the incrementing of the first value based on a first bit value representation, the first bit value representation corresponding to a first audience member identifier; incrementing, by executing an instruction with the processor, a second value corresponding to a second position in the vector, the incrementing of the second value based on a second bit value representation, the second bit value representation corresponding to a second audience member; estimating, by executing an instruction with the processor, a second frequency moment of media impression data using the vector; determining, by executing an instruction with the processor, a variance of the second frequency moment; and based on the second frequency moment, executing a query of the media impression data with the processor at a scheduled time. 16. The method of claim 15 , further including: determining a first result by squaring the second frequency moment; doubling the first result; determining a second result by subtracting one from a number of positions in the vector; and determining a ratio of the first result and the second result. 17. The method of claim 16 , wherein the number of positions in the vector is based on a target precision threshold. 18. The method of claim 17 , further including determining whether to update the target precision threshold after determining whether the processor can complete the query of the media impression data based on a query processing constraint. 19. The method of claim 18 , further including, based on a request for a more accurate second frequency moment, determining not to update the target precision threshold. 20. The method of claim 18 , wherein the query processing constraint includes at least one of a scheduling constraint, available memory utilization, or an available processing resource. 21. The method of claim 15 , further including obtaining the media impression data from an audience metrics database, the media impression data corresponding to an audience member total for a media item.
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