US 12,455,778 B2
Systems and methods for data stream simulation
Mark Watson, Urbana, IL (US); Anh Truong, Champaign, IL (US); Fardin Abdi Taghi Abad, Champaign, IL (US); Jeremy Goodsitt, Champaign, IL (US); Austin Walters, Savoy, IL (US); Michael Walters, Brooklyn, NY (US); Noriaki Tatsumi, Silver Spring, MD (US); and Kate Key, Effingham, IL (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Oct. 4, 2018, as Appl. No. 16/151,431.
Claims priority of provisional application 62/694,968, filed on Jul. 6, 2018.
Prior Publication US 2020/0012890 A1, Jan. 9, 2020
Int. Cl. G06N 3/094 (2023.01); G06F 8/71 (2018.01); G06F 9/54 (2006.01); G06F 11/3604 (2025.01); G06F 11/362 (2025.01); G06F 16/22 (2019.01); G06F 16/242 (2019.01); G06F 16/2455 (2019.01); G06F 16/248 (2019.01); G06F 16/25 (2019.01); G06F 16/28 (2019.01); G06F 16/335 (2019.01); G06F 16/903 (2019.01); G06F 16/9032 (2019.01); G06F 16/9038 (2019.01); G06F 16/906 (2019.01); G06F 16/93 (2019.01); G06F 17/15 (2006.01); G06F 17/16 (2006.01); G06F 17/18 (2006.01); G06F 18/20 (2023.01); G06F 18/21 (2023.01); G06F 18/2115 (2023.01); G06F 18/213 (2023.01); G06F 18/214 (2023.01); G06F 18/22 (2023.01); G06F 18/23 (2023.01); G06F 18/24 (2023.01); G06F 18/2411 (2023.01); G06F 18/2415 (2023.01); G06F 18/40 (2023.01); G06F 21/55 (2013.01); G06F 21/60 (2013.01); G06F 21/62 (2013.01); G06F 30/20 (2020.01); G06F 40/117 (2020.01); G06F 40/166 (2020.01); G06F 40/20 (2020.01); G06N 3/04 (2023.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/06 (2006.01); G06N 3/08 (2023.01); G06N 3/088 (2023.01); G06N 5/00 (2023.01); G06N 5/02 (2023.01); G06N 5/04 (2023.01); G06N 7/00 (2023.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06Q 10/04 (2023.01); G06T 7/194 (2017.01); G06T 7/246 (2017.01); G06T 7/254 (2017.01); G06T 11/00 (2006.01); G06V 10/70 (2022.01); G06V 10/98 (2022.01); G06V 30/194 (2022.01); G06V 30/196 (2022.01); H04L 9/40 (2022.01); H04L 67/00 (2022.01); H04L 67/306 (2022.01); H04N 21/234 (2011.01); H04N 21/81 (2011.01)
CPC G06F 9/541 (2013.01) [G06F 8/71 (2013.01); G06F 9/54 (2013.01); G06F 9/547 (2013.01); G06F 11/3608 (2013.01); G06F 11/3628 (2013.01); G06F 11/3636 (2013.01); G06F 16/2237 (2019.01); G06F 16/2264 (2019.01); G06F 16/2423 (2019.01); G06F 16/24568 (2019.01); G06F 16/248 (2019.01); G06F 16/254 (2019.01); G06F 16/258 (2019.01); G06F 16/283 (2019.01); G06F 16/285 (2019.01); G06F 16/288 (2019.01); G06F 16/335 (2019.01); G06F 16/90332 (2019.01); G06F 16/90335 (2019.01); G06F 16/9038 (2019.01); G06F 16/906 (2019.01); G06F 16/93 (2019.01); G06F 17/15 (2013.01); G06F 17/16 (2013.01); G06F 17/18 (2013.01); G06F 18/2115 (2023.01); G06F 18/213 (2023.01); G06F 18/214 (2023.01); G06F 18/2148 (2023.01); G06F 18/217 (2023.01); G06F 18/2193 (2023.01); G06F 18/22 (2023.01); G06F 18/23 (2023.01); G06F 18/24 (2023.01); G06F 18/2411 (2023.01); G06F 18/2415 (2023.01); G06F 18/285 (2023.01); G06F 18/40 (2023.01); G06F 21/552 (2013.01); G06F 21/60 (2013.01); G06F 21/6245 (2013.01); G06F 21/6254 (2013.01); G06F 30/20 (2020.01); G06F 40/117 (2020.01); G06F 40/166 (2020.01); G06F 40/20 (2020.01); G06N 3/04 (2013.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/06 (2013.01); G06N 3/08 (2013.01); G06N 3/088 (2013.01); G06N 3/094 (2023.01); G06N 5/00 (2013.01); G06N 5/02 (2013.01); G06N 5/04 (2013.01); G06N 7/00 (2013.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06Q 10/04 (2013.01); G06T 7/194 (2017.01); G06T 7/246 (2017.01); G06T 7/248 (2017.01); G06T 7/254 (2017.01); G06T 11/001 (2013.01); G06V 10/768 (2022.01); G06V 10/993 (2022.01); G06V 30/194 (2022.01); G06V 30/1985 (2022.01); H04L 63/1416 (2013.01); H04L 63/1491 (2013.01); H04L 67/306 (2013.01); H04L 67/34 (2013.01); H04N 21/23412 (2013.01); H04N 21/8153 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A cloud computing system for generating a synthetic data stream, comprising:
at least one processor; and
at least one non-transitory memory storing instructions that, when executed by the at least one processor, cause the cloud computing system to perform operations comprising:
receiving, from an interface, a request to generate a synthetic data stream, the request indicating a reference data stream from a stream source;
receiving, from the interface, a correlation metric for the reference synthetic data stream; and
generating a synthetic data stream that tracks the reference data stream, wherein the generating comprises repeatedly updating data models of the reference data stream at predetermined time intervals, a repeat comprising:
retrieving, from a model storage, a current data model of the reference data stream, the current data model comprising a generative adversarial network that generates an output resembling current characteristics of the reference data stream;
generating the synthetic data stream using the current data model of the reference data stream;
generating a new data model of the reference data stream;
evaluating performance criteria of the new data model by one or more duplicate elements in the synthetic data stream and the reference data stream, a prevalence of a common value in the synthetic data stream and the reference data stream, a maximum difference of rare values in the synthetic data stream and the reference data stream, and differences in schema between the synthetic data stream and the reference data stream;
storing, in the model storage, the new data model; and
updating, in the model storage, the current data model with the new data model.