IP Library Granted Patent US 11,551,290
Granted Patent B2
US 11,551,290 · App. 17/175,742 · Granted Jan 10, 2023

Systems and methods for machine-based matching of lodging inventory from disparate reservation provider systems

Inventors: Ryan Williams (Lehi, UT); Ryan McCoy (Lehi, UT); Daniel Nelson (Lehi, UT); Neil Valentine (Lehi, UT); Scott Jensen (Lehi, UT)
Assignee: TravelPass Group, LLC
G06Q30/0643G06F16/9535G06Q10/02G06Q30/0629G06Q30/0633G06Q50/12
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Quick Facts
Patent No.
US 11,551,290
App. No.
17/175,742
Granted
Jan 10, 2023
Kind
B2
Abstract

Systems and methods for machine-based matching of lodging inventory from a plurality of disparate reservation provider systems address the difficulties inherent in comparing prices to obtain a lowest possible price, which difficulties are inherent in the distribution of inventory to multiple third-party reservation providers who are generally permitted to utilize their own naming conventions when describing lodging inventory and who are also free to at least some extent to set prices for the various lodging inventory within their control. The systems and methods match room types using information obtained from the multiple third-party reservation providers, whereby direct comparisons can be made between prices for the same room types even when the reservation providers do not utilize identical descriptions or naming conventions for the respective room inventories.

Claims (58)

1. A method, comprising:

receiving a plurality of room descriptions for rooms of a first lodging facility, each room description from the plurality of room descriptions including price information and a provider-specific description of the room, wherein the plurality of room descriptions includes:

a first set of room descriptions from a first provider system associated with one or more rooms of the first lodging facility; and

a second set of room descriptions from a second provider system associated with the one or more rooms of the first lodging facility;

maintaining a room definition storage including a plurality of room definition sets for the first lodging facility, the plurality of room definition sets indicating including a first room definition defining characteristics of a first class of rooms and a second room definition set defining characteristics of a second class of rooms;

applying a correlation model to the plurality of room descriptions to identify a first grouping of room descriptions including a first one or more room descriptions from the first set of room descriptions and a second one or more room descriptions from the second set of room descriptions, wherein the correlation model is trained to correlate a given room description with a corresponding room definition set from the room definition storage; and

generating a first consumer-ready room description for a first one or more rooms of the first lodging facility based on the first one or more room descriptions and the second one or more room descriptions.

2. The method of claim 1 , wherein the provider-specific description of the room includes a description of the room generated by a corresponding reservation provider.

3. The method of claim 1 , wherein the consumer-ready room description includes a combination of price information from a first room description from the first set of room descriptions and a provider-specific description from a second room description from the second set of room descriptions.

4. The method of claim 3 ,

wherein the consumer-ready room description includes the price information from the first room description based on the price information from the room description having a lower price than the price information from the second room description, and

wherein the consumer-ready room description includes the provider-specific description from the second room description based on the provider-specific description from the second room description having more detail than a provider.

5. The method of claim 1 , wherein a first room description from the first set of room descriptions and a second room description from the second set of room descriptions is associated with a same room or set of rooms of the same room class for the first lodging facility.

6. The method of claim 1 , wherein the correlation model is a machine learning model trained on a dataset of known correlations between a plurality of training room descriptions and associated room definitions sets.

7. The method of claim 1 , further comprising:

applying the correlation model to the plurality of room descriptions to identify a second grouping of room descriptions including a third one or more room descriptions from the first set of room descriptions and a fourth one or more room descriptions from the second set of room descriptions; and

generating a second consumer-ready room description for a second one or more rooms of the first lodging facility based on the third one or more room descriptions and the fourth one or more room descriptions.

8. The method of claim 1 , wherein generating the first consumer-ready room description includes:

parsing provider-specific descriptions of room descriptions from the first grouping of room descriptions to identify a provider-specific description having a higher level of detail than one or more additional provider-specific descriptions within the first grouping of room descriptions; and

identifying a lowest price from the price information from the room descriptions for the first grouping of room descriptions.

9. The method of claim 8 , wherein the first consumer-ready room description includes the identified provider-specific description having the higher level of detail and the lowest price.

10. The method of claim 9 , wherein the provider-specific description having the higher level of detail and the lowest price are from different room descriptions associated with different lodging facilities.

11. A system, comprising:

one or more processors;

memory in electronic communication with the one or more processors; and

instructions stored in the memory, the instructions being executable by the one or more processors to:

receiving a plurality of room descriptions for rooms of a first lodging facility, each room description from the plurality of room descriptions including price information and a provider-specific description of the room, wherein the plurality of room descriptions includes:

a first set of room descriptions from a first provider system associated with one or more rooms of the first lodging facility; and

a second set of room descriptions from a second provider system associated with the one or more rooms of the first lodging facility;

maintaining a room definition storage including a plurality of room definition sets for the first lodging facility, the plurality of room definition sets indicating including a first room definition defining characteristics of a first class of rooms and a second room definition set defining characteristics of a second class of rooms;

applying a correlation model to the plurality of room descriptions to identify a first grouping of room descriptions including a first one or more room descriptions from the first set of room descriptions and a second one or more room descriptions from the second set of room descriptions, wherein the correlation model is trained to correlate a given room description with a corresponding room definition set from the room definition storage; and

generating a first consumer-ready room description for a first one or more rooms of the first lodging facility based on the first one or more room descriptions and the second one or more room descriptions.

12. The system of claim 11 , wherein the consumer-ready room description includes a combination of price information from a first room description from the first set of room descriptions and a provider-specific description from a second room description from the second set of room descriptions.

13. The system of claim 12 ,

wherein the consumer-ready room description includes the price information from the first room description based on the price information from the room description having a lower price than the price information from the second room description, and

wherein the consumer-ready room description includes the provider-specific description from the second room description based on the provider-specific description from the second room description having more detail than a provider.

14. The system of claim 11 , wherein a first room description from the first set of room descriptions and a second room description from the second set of room descriptions is associated with a same room or set of rooms of the same room class for the first lodging facility.

15. The system of claim 11 , wherein the correlation model is a machine learning model trained on a dataset of known correlations between a plurality of training room descriptions and associated room definitions sets.

16. The system of claim 11 , wherein the instructions are further executable by the one or more processors to:

apply the correlation model to the plurality of room descriptions to identify a second grouping of room descriptions including a third one or more room descriptions from the first set of room descriptions and a fourth one or more room descriptions from the second set of room descriptions; and

generate a second consumer-ready room description for a second one or more rooms of the first lodging facility based on the third one or more room descriptions and the fourth one or more room descriptions.

17. The system of claim 11 , wherein generating the first consumer-ready room description includes:

parsing provider-specific descriptions of room descriptions from the first grouping of room descriptions to identify a provider-specific description having a higher level of detail than one or more additional provider-specific descriptions within the first grouping of room descriptions; and

identifying a lowest price from the price information from the room descriptions for the first grouping of room descriptions.

18. The system of claim 17 ,

wherein the first consumer-ready room description includes the identified provider-specific description having the higher level of detail and the lowest price, and

wherein the provider-specific description having the higher level of detail and the lowest price are from different room descriptions associated with different lodging facilities.

19. A non-transitory computer readable medium storing instructions thereon that, when executed by one or more processors, causes a computing system to:

receive a plurality of room descriptions for rooms of a first lodging facility, each room description from the plurality of room descriptions including price information and a provider-specific description of the room, wherein the plurality of room descriptions includes:

a first set of room descriptions from a first provider system associated with one or more rooms of the first lodging facility; and

a second set of room descriptions from a second provider system associated with the one or more rooms of the first lodging facility;

maintain a room definition storage including a plurality of room definition sets for the first lodging facility, the plurality of room definition sets indicating including a first room definition defining characteristics of a first class of rooms and a second room definition set defining characteristics of a second class of rooms;

apply a correlation model to the plurality of room descriptions to identify a first grouping of room descriptions including a first one or more room descriptions from the first set of room descriptions and a second one or more room descriptions from the second set of room descriptions, wherein the correlation model is trained to correlate a given room description with a corresponding room definition set from the room definition storage; and

generate a first consumer-ready room description for a first one or more rooms of the first lodging facility based on the first one or more room descriptions and the second one or more room descriptions.

20. The non-transitory computer readable medium of claim 19 ,

wherein the consumer-ready room description includes a combination of price information from a first room description from the first set of room descriptions and a provider-specific description from a second room description from the second set of room descriptions,

wherein the consumer-ready room description includes the price information from the first room description based on the price information from the room description having a lower price than the price information from the second room description, and

wherein the consumer-ready room description includes the provider-specific description from the second room description based on the provider-specific description from the second room description having more detail than a provider.

Assignments (4)
CORRECTIVE ASSIGNMENT TO CORRECT THE NAME AND ADDRESS OF THE ASSIGNEE PREVIOUSLY RECORDED ON REEL 70774 FRAME 935. ASSIGNOR(S) HEREBY CONFIRMS THE SECURITY INTEREST. Recorded Apr 10, 2025
From: TRAVELPASS GROUP, INC.
To: HILLCREST BANK, A DIVISION OF NBH BANK, A COLORADO STATE BANK
Reel/Frame 070996/0465 →
SECURITY INTEREST Recorded Apr 8, 2025
From: TRAVELPASS GROUP, INC.
To: HILLCREST BANK, A DIVISION OF NBH BANK
Reel/Frame 070774/0935 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 11, 2022
From: WILLIAMS, RYAN; MCCOY, RYAN; NELSON, DANIEL; VALENTINE, NEIL; JENSEN, SCOTT
To: RESERVATION COUNTER, LLC
Reel/Frame 060786/0722 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 11, 2022
From: RESERVATION COUNTER, LLC
To: TRAVELPASS GROUP, LLC
Reel/Frame 060786/0824 →
Continuity (3)
Continuation 16042605 · Jul 23, 2018
Provisional Application 62536781 · Jul 25, 2017
Related Publication 20210166301A1 · Jun 3, 2021