US 12,346,941 B2
Method, apparatus, and computer program product for determining closing metrics
Brian Mullins, Chicago, IL (US); Matt DeLand, San Francisco, CA (US); Zahra Ferdowsi, Chicago, IL (US); Stephen Lang, Chicago, IL (US); John Stokvis, Chicago, IL (US); Nolan Finn, Chicago, IL (US); and Shafiq Shariff, Chicago, IL (US)
Assigned to Bytedance Inc., Wilmington, DE (US)
Filed by Bytedance Inc., Wilmington, DE (US)
Filed on Jun. 20, 2024, as Appl. No. 18/748,962.
Application 18/748,962 is a continuation of application No. 17/375,428, filed on Jul. 14, 2021, granted, now 12,026,757.
Application 17/375,428 is a continuation of application No. 15/667,666, filed on Aug. 3, 2017, granted, now 11,120,345, issued on Sep. 14, 2021.
Application 15/667,666 is a continuation of application No. 15/051,165, filed on Feb. 23, 2016, granted, now 10,558,922, issued on Feb. 11, 2020.
Application 15/051,165 is a continuation of application No. 13/826,757, filed on Mar. 14, 2013, granted, now 9,330,357, issued on May 3, 2016.
Claims priority of provisional application 61/730,046, filed on Nov. 26, 2012.
Claims priority of provisional application 61/709,623, filed on Oct. 4, 2012.
Prior Publication US 2024/0420190 A1, Dec. 19, 2024
Int. Cl. G06Q 30/0282 (2023.01); G06N 5/02 (2023.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01); G06N 20/10 (2019.01); G06Q 10/0631 (2023.01); G06Q 10/0635 (2023.01); G06Q 10/0639 (2023.01); G06Q 10/067 (2023.01); G06Q 30/0201 (2023.01); G06Q 30/0202 (2023.01); G06Q 30/0601 (2023.01); G06Q 40/00 (2023.01)
CPC G06Q 30/0282 (2013.01) [G06N 5/02 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06N 20/10 (2019.01); G06Q 10/06311 (2013.01); G06Q 10/06315 (2013.01); G06Q 10/0635 (2013.01); G06Q 10/0639 (2013.01); G06Q 10/06393 (2013.01); G06Q 10/067 (2013.01); G06Q 30/0201 (2013.01); G06Q 30/0202 (2013.01); G06Q 30/0609 (2013.01); G06Q 40/00 (2013.01)] 19 Claims
OG exemplary drawing
 
1. An apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least:
classify providers based on a return rate of a provider;
generate a plurality of attributes corresponding to the provider by normalizing a plurality of raw data;
supply a classifying model with a dataset, wherein the dataset comprises an identification of a provider and the plurality of attributes corresponding to the provider;
identify a class of the provider in accordance with the plurality of corresponding attributes, wherein the identification is determined based on one or more patterns determinative of a return rate by the classifying model; and
identify a subset of the plurality of corresponding attributes determinative of an improved classification;
train the classifying model in accordance with the subset of the plurality of corresponding attributes; and
determine a probability of close with a particular provider, wherein the probability of close indicates the probability that the particular provider will contract with a promotion service to offer a promotion within a respective time period, wherein the promotion is offered to a consumer for purchase from the promotion service in exchange for at least one of a discounted service or a discounted product from the provider.