US 11,676,184 B2
Subscription based travel service
Brent Handler, Englewood, CO (US); Cody Holloway, Denver, CO (US); Jesus Gandarilla, Westminster, CO (US); Rodolfo Rodriguez, Denver, CO (US); Ashley Roybal, Denver, CO (US); Christopher Smith, Denver, CO (US); and Brad Handler, Denver, CO (US)
Assigned to INSPIRATO, LLC, Denver, CO (US)
Filed by Inspirato LLC, Denver, CO (US)
Filed on Jun. 2, 2021, as Appl. No. 17/336,574.
Application 17/336,574 is a continuation of application No. 16/390,752, filed on Apr. 22, 2019, granted, now 11,055,753.
Prior Publication US 2021/0287266 A1, Sep. 16, 2021
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 30/0283 (2023.01); G06Q 10/02 (2012.01); G06Q 20/28 (2012.01); G06Q 50/14 (2012.01)
CPC G06Q 30/0283 (2013.01) [G06Q 10/02 (2013.01); G06Q 20/28 (2013.01); G06Q 50/14 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A method comprising:
receiving, by one or more processors, experience related information with a future experience date for a user;
computing, by the one or more processors, a subscription value as a function of the future experience date and a second date, the subscription value comprising an amortized value portion, the subscription value representing an amount of resources that will be available to be used for accessing an experience on the future experience date;
determining a minimum experience value and a maximum purchase amount based on the subscription value;
training a machine learning technique to process training data comprising data associated with a plurality of users and to establish a relationship between historical user activity information and classifications of the plurality of users by processing the training data further comprising the historical user activity information derived from the plurality of users, the training being performed by:
retrieving a portion of the training data from a storage device;
extracting features from the training data for the plurality of users;
utilizing the machine learning technique to estimate an attribute for the plurality of users based on the features, as extracted; and
updating parameters of the machine learning technique based on the attribute, as estimated, for the plurality of users;
searching, based on the subscription value, a plurality of experience related resources that are available for access on the future experience date to identify candidate experience related resources, each of the candidate experience related resources being associated with a first cost that exceeds the minimum experience value and is within the maximum purchase amount; and
applying the machine learning technique to user information associated with the user to generate a classification for the user;
identifying, based on an output of the machine learning technique comprising the classification for the user, a subset of the candidate experience related resources, the subset of the candidate experience related resources being presented to the user via an interface, wherein identifying the subset further comprises:
identifying, by the one or more processors, the subset of the candidate experience related resources that each have a second cost that is less than the maximum purchase amount.