IP Library Granted Patent US 11,710,418
Granted Patent B2
US 11,710,418 · App. 16/797,692 · Granted Jul 25, 2023

Education-based nomadic sequencing recommendations for families

Inventors: Joao Pedro Carvalho Oliveira de Miranda Reis (San Francisco, CA); Cynthia Yue Chen (San Francisco, CA); Sara Louise Sodine (San Francisco, CA); Dan Young Li (San Francisco, CA)
Assignee: Airbnb, Inc.
G09B5/02G06Q10/02G06Q10/1093
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Quick Facts
Patent No.
US 11,710,418
App. No.
16/797,692
Granted
Jul 25, 2023
Kind
B2
Abstract

A system and a method are disclosed for augmenting a required curriculum of an individual in a nomadic group. The system retrieves, from a client device, a request for an accommodation recommendation from the nomadic group, which includes an individual with a required curriculum. The system maps the curriculum to destinations in a destination database and determines a set of geographic regions including the destinations. The system optimizes an accommodation recommendation based on available listings in the geographic regions and geographic locations of the destinations and transmits, for display on a user interface at the client device, a user interface comprising the accommodation recommendation.

Claims (73)

1. A computer-implemented method for augmenting a required curriculum of an individual in a nomadic group, the method comprising:

receiving, from a client device by an accommodation management system, a request for an accommodation recommendation, the request including a time period and a required curriculum;

determining a set of destinations that satisfy the required curriculum over the time period by performing operations comprising:

analyzing, using a machine learning model trained to generate a percentage match to a destination, information describing the required curriculum in a curriculum database;

generating, by the machine learning model, a percentage match to each destination in a destination database; and

selecting destinations with a percentage match above a predetermined threshold value to comprise the set of destinations;

grouping destinations in the set of destinations by geographic region;

selecting one or more geographic regions for subsets of the time period based on travel requirements for the required curriculum and at least one of: user preference information retrieved from a user profile database, a size of a group for travel, a geographic region, travel experience of one or more user in the group for travel, or an amount of travel requested by one or more user in the group for travel;

for each selected geographic region and corresponding subset of the time period, determining one or more listings for accommodations available in the selection geographic region during the subset of the time period;

optimizing the accommodation recommendation based on the determined one or more listings in each selected geographic region using a weighted combination of user preference information of each user in the group for travel as stored in the user profile database and listing information in a listing database that includes listing information for each listing; and

transmitting, for display on a user interface at the client device, the accommodation recommendation.

2. The computer-implemented method of claim 1 , wherein optimizing the accommodation recommendation further comprises:

booking a listing of the accommodation recommendation by populating a booking data structure for the listing with user account data for a user of the client device;

transmitting, for display on the client device, an indication that the listing was booked.

3. The computer-implemented method of claim 1 , wherein

selecting one or more geographic regions further includes determining geographic locations corresponding to a threshold number of topics in the required curriculum.

4. The computer-implemented method of claim 1 , wherein topics of the required curriculum correspond to sequences of time in an academic year, the method further comprising:

determining, for each sequence, an accommodation recommendation; and

transmitting, for display on the user interface at the client device, an itinerary including the accommodation recommendation for each sequence.

5. The computer-implemented method of claim 4 , wherein determining, for each sequence, an accommodation recommendation comprises:

minimizing a distance metric between each accommodation recommendation.

6. The computer-implemented method of claim 4 , the method further comprising:

responsive to a sequence being within a threshold amount of time, booking a listing of the accommodation recommendation for the sequence by populating a booking data structure for the listing with user account data for a user of the client device.

7. The computer-implemented method of claim 1 , wherein the request includes information describing an age of the individual, and the method further comprises:

retrieving, from an external database, a required curriculum for the age of the individual.

8. The computer-implemented method of claim 1 , wherein the request includes information describing the required curriculum.

9. The computer-implemented method of claim 1 , wherein the accommodation recommendation includes a listing, enhanced education destinations, and topics of the required curriculum related to the enhanced education destinations.

10. A system for augmenting a required curriculum of an individual in a nomadic group, system comprising:

at least one processor;

a memory storing instructions that when executed cause the processor to perform operations comprising:

receiving, from a client device by an accommodation management system, a request for an accommodation recommendation, the request including a time period and a required curriculum;

determining a set of destinations that satisfy the required curriculum over the time period by performing operations comprising:

analyzing, using a machine learning model trained to generate a percentage match to a destination, information describing the required curriculum in a curriculum database;

generating, by the machine learning model, a percentage match to each destination in a destination database; and

selecting destinations with a percentage match above a predetermined threshold value to comprise the set of destinations;

grouping destinations in the set of destinations by geographic region;

selecting one or more geographic regions for subsets of the time period based on travel requirements for the required curriculum and at least one of: user preference information retrieved from a user profile database, a size of a group for travel, a geographic region, travel experience of one or more user in the group for travel, or an amount of travel requested by one or more user in the group for travel;

for each selected geographic region and corresponding subset of the time period, determining one or more listings for accommodations available in the selection geographic region during the subset of the time period;

optimizing the accommodation recommendation based on the determined one or more listings in each selected geographic region using a weighted combination of user preference information of each user in the group for travel as stored in the user profile database and listing information in a listing database that includes listing information for each listing; and

transmitting, for display on a user interface at the client device, the accommodation recommendation.

11. The system of claim 10 , wherein the operations further comprise:

booking a listing of the accommodation recommendation by populating a booking data structure for the listing with user account data for a user of the client device; and

transmitting, for display on a user interface at the client device, an indication that the listing was booked.

12. The system of claim 10 , wherein

selecting one or more geographic regions further includes determining geographic locations corresponding to a threshold number of topics in the required curriculum.

13. The system of claim 10 , wherein topics of the required curriculum correspond to sequences of time in an academic year, and the operations further comprise:

determining, for each sequence, an accommodation recommendation; and

transmitting, for display on the user interface of the client device, an itinerary including the accommodation recommendation for each sequence.

14. The system of claim 13 , wherein determining, for each sequence, an accommodation recommendation further comprises:

minimizing a distance metric between each accommodation recommendation.

15. The system of claim 13 , the operations further comprising:

responsive to a sequence being within a threshold amount of time, booking a listing of the accommodation recommendation for the sequence by populating a booking data structure for the listing with user account data for a user of the client device.

16. A non-transitory computer readable medium configured to store instructions, the instructions when executed by a processor cause the processor to perform operations comprising:

receiving, from a client device by an accommodation management system, a request for an accommodation recommendation, the request including a time period and a required curriculum;

determining a set of destinations that satisfy the required curriculum over the time period by performing operations comprising:

analyzing, using a machine learning model trained to generate a percentage match to a destination, information describing the required curriculum in a curriculum database;

generating, by the machine learning model, a percentage match to each destination in a destination database; and

selecting destinations with a percentage match above a predetermined threshold value to comprise the set of destinations;

grouping destinations in the set of destinations by geographic region;

selecting one or more geographic regions for subsets of the time period based on travel requirements for the required curriculum and at least one of: user preference information retrieved from a user profile database, a size of a group for travel, a geographic region, travel experience of one or more user in the group for travel, or an amount of travel requested by one or more user in the group for travel;

for each selected geographic region and corresponding subset of the time period, determining one or more listings for accommodations available in the selection geographic region during the subset of the time period;

optimizing the accommodation recommendation based on the determined one or more listings in each selected geographic region using a weighted combination of user preference information of each user in the group for travel as stored in the user profile database and listing information in a listing database that includes listing information for each listing; and

transmitting, for display on a user interface at the client device, the accommodation recommendation.

17. The non-transitory computer-readable medium of claim 16 , the operations further comprising:

booking a listing of the accommodation recommendation by populating a booking data structure for the listing with user account data for a user of the client device; and

transmitting, for display on the user interface at the client device, an indication that the listing was booked.

18. The non-transitory computer-readable medium of claim 16 , wherein

selecting one or more geographic regions further includes determining geographic locations corresponding to a threshold number of topics in the required curriculum.

19. The non-transitory computer-readable medium of claim 16 , wherein topics of the required curriculum correspond to sequences of time in an academic year, and the operations further comprise:

determining, for each sequence, an accommodation recommendation; and

transmitting, for display on the user interface of the client device, an itinerary including the accommodation recommendation for each sequence.

20. The non-transitory computer-readable medium of claim 19 , wherein determining, for each sequence, an accommodation recommendation further comprises:

minimizing a distance metric between each accommodation recommendation.

Assignments (7)
RELEASE (REEL 054586 / FRAME 0033) Recorded Nov 1, 2022
From: MORGAN STANLEY SENIOR FUNDING, INC.
To: AIRBNB, INC.
Reel/Frame 061825/0910 →
RELEASE OF SECURITY INTEREST IN PATENTS Recorded Apr 21, 2021
From: TOP IV TALENTS, LLC
To: AIRBNB, INC.
Reel/Frame 055997/0907 →
RELEASE OF SECURITY INTEREST Recorded Mar 8, 2021
From: CORTLAND CAPITAL MARKET SERVICES LLC
To: AIRBNB, INC.
Reel/Frame 055527/0531 →
SECURITY AGREEMENT Recorded Nov 19, 2020
From: AIRBNB, INC.
To: MORGAN STANLEY SENIOR FUNDING, INC.
Reel/Frame 054586/0033 →
FIRST LIEN SECURITY AGREEMENT Recorded Apr 21, 2020
From: AIRBNB, INC.
To: CORTLAND CAPITAL MARKET SERVICES LLC
Reel/Frame 052456/0036 →
SECOND LIEN PATENT SECURITY AGREEMENT Recorded Apr 17, 2020
From: AIRBNB, INC.
To: TOP IV TALENTS, LLC, AS COLLATERAL AGENT
Reel/Frame 052433/0416 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 21, 2020
From: REIS, JOAO PEDRO CARVALHO OLIVEIRA DE MIRANDA; CHEN, CYNTHIA YUE; SODINE, SARA LOUISE; LI, DAN YOUNG
To: AIRBNB, INC.
Reel/Frame 051893/0137 →