Method and system for a pre-shopping reservation system with increased search efficiency

• US 9,098,881 B2
• Filed: 07/18/2011
• Issued: 08/04/2015
• Est. Priority Date: 06/27/2011
• Status: Active Grant

• Current Assignee: Amadeus (Amadeus Global Travel Distribution S.A.)
• Original Assignee: Amadeus (Amadeus Global Travel Distribution S.A.)
• Inventors: Ciabrini, Damien, Reynaud, Claudine, Legrand, Guillaume, Isnardy, Luc, Gole, Rmy
• Primary Examiner(s): Jung, Allen J
• Application Number:
  US13/185,417
• Publication Number:
  US 20120330693A1
• Time in Patent Office: 1,478 Days
• Field of Search: 705/5
• US Class Current: 1/1
• CPC Class Codes: G06Q 10/02 Reservations, e.g. for tickets, services or events
• CPC Class Codes: G06Q 50/14 Travel agencies

Abstract

The method according to a preferred embodiment of the present invention provides a pre-shopping reservation tool which allows storing entire catalogs of air travels from many providers, while ensuring a high cache accuracy at limited operational costs. The system makes use of the fares knowledge to merge identical travel recommendations coming from different travel providers (airline, travel agencies) when possible, i.e. when fares are public and not negotiated for a specific travel provider. This prevents redundant prices to be stored in the system and improves its cost effectiveness. The system according to a preferred embodiment of the present invention relies on several dedicated data analysis engines to optimize the cost of data pre-computations while at the same time maintaining good data accuracy.

Claims

1. A computer program product comprising:

a non-transitory computer readable medium; and

program code stored on the computer readable storage medium that, when executed by a processor, causes the processor to;

store a plurality of pre-computed travel recommendations in a fast access memory of the computer, each pre-computed travel recommendation comprising a price of the travel recommendation;

assign a score to each pre-computed travel recommendation, the score indicative of a frequency with which the corresponding pre-computed travel recommendation is re-computed;

select one or more of the plurality of pre-computed travel recommendations for re-computing based on the assigned scores;

launch a query in the plurality of travel databases to obtain data relating to the selected pre-computed travel recommendations;

re-compute the selected pre-computed travel recommendations based on the data obtained by the query;

determine a frequency with which the price of the selected pre-computed travel recommendations changes over a first span of dates including a punctual event;

determine the frequency with which the price of the selected pre-computed travel recommendations changes over a second span of dates not including the punctual event;

adjust the score of the selected pre-computed travel recommendations based on whether the current date falls in the first span or the second span of dates;

in response to receiving the travel query, search within the plurality of pre-computed travel recommendations in the fast access memory of the computer for travel recommendations that satisfy the parameters included in the travel query; and

issue a response to the user for the travel query, the response including the pre-computed travel recommendations satisfying the parameters included in the travel query.

2. A method for providing priced travel recommendations according to a travel query from a user, the travel query received by a computer having one or more processors and access to a plurality of travel databases, the travel query including one or more parameters, the method comprising:

storing a plurality of pre-computed travel recommendations in a fast access memory of the computer by at least one of the processors, each pre-computed travel recommendation comprising a price of the travel recommendation;

assigning a score to each pre-computed travel recommendation by at least one of the processors, the score indicative of a frequency with which the corresponding pre-computed travel recommendation is re-computed;

determining a frequency with which the price of the corresponding pre-computed travel recommendation changes over a first span of dates including a punctual event;

determining a frequency with which the price of the corresponding pre-computed travel recommendation changes over a second span of dates not including the punctual event;

adjusting the score of the corresponding pre-computed travel recommendation based on whether the current date falls in the first span or the second span of dates;

selecting one or more of the plurality of pre-computed travel recommendations for recomputation by at least one of the processors based on the assigned scores;

launching a query in the plurality of travel databases by at least one of the processors to obtain data relating to the selected pre-computed travel recommendations;

re-computing the selected pre-computed travel recommendations by at least one of the processors based on the data obtained by the query;

in response to receiving the travel query, searching by at least one of the processors within the plurality of pre-computed travel recommendations in the fast access memory of the computer for travel recommendations that satisfy the parameters included in the travel query; and

issuing a response to the user by at least one of the one or more processors, the response including one or more of the pre-computed travel recommendations satisfying the parameters included in the travel query.

3. The method of claim 2 wherein the score indicative of the frequency with which the corresponding pre-computed travel recommendation is re-computed is based at least in part on a value indicative of a volatility of the price of the travel recommendation.

4. The method of claim 2 wherein the score indicative of the frequency with which the corresponding pre-computed recommendation is re-computed includes a value indicative of a popularity of the travel recommendation.

5. The method of claim 2 wherein launching the query in the plurality of travel databases and re-computing the selected pre-computed travel recommendations is done by a dedicated sub-system.

6. The method of claim 2 further comprising:

dividing the plurality of pre-computed travel recommendations into a plurality of homogeneous groups, each pre-computed travel recommendation in a homogeneous group having at least one parameter with the same value, and storing each group in one of a plurality of fast access memory locations.

7. The method of claim 2 wherein launching the query in the plurality of travel databases to obtain data relating to the selected pre-computed travel recommendations is done at a predetermined time interval.

8. The method of claim 2 wherein the query in the plurality of travel databases to obtain data relating to the selected pre-computed travel recommendations is done with a batch process.

9. The method of claim 2 further comprising:

indexing the plurality of pre-computed travel recommendations according to a multi-dimensional data structure.

10. The method of claim 2 further comprising:

in response to none of the pre-computed travel recommendations satisfying the parameters included in the travel query received from the user, searching within the plurality of pre-computed travel recommendations for travel recommendations that satisfy a travel query with relaxed constraints on one or more of the parameters included in the user travel query.

11. The method of claim 2 further comprising:

in response to none of the pre-computed travel recommendations satisfying the parameters included in the travel query received from the user, issuing an alert message to the user.

12. A method for providing priced travel recommendations according to a travel query from a user, the travel query received by a computer having one or more processors and access to a plurality of travel databases, the travel query including one or more parameters, the method comprising:

storing a plurality of pre-computed travel recommendations in a fast access memory of the computer by at least one of the processors, each pre-computed travel recommendation comprising a price of the travel recommendation;

assigning a score to each pre-computed travel recommendation by at least one of the processors, wherein the score is indicative of a frequency with which the corresponding pre-computed travel recommendation is re-computed, and wherein the score indicative of the frequency with which the corresponding pre-computed travel recommendation is re-computed is based at least in part on a value indicative of a volatility of the price of the travel recommendation;

determining the volatility of the price of the corresponding pre-computed travel recommendation by comparing a price previously stored for the pre-computed travel recommendation to the price for the re-computed travel recommendation, and adjusting the volatility of the price of the corresponding pre-computed travel recommendation based on a difference between the stored and re-computed prices;

selecting one or more of the plurality of pre-computed travel recommendations for recomputation by at least one of the processors based on the assigned scores;

launching a query in the plurality of travel databases by at least one of the processors to obtain data relating to the selected pre-computed travel recommendations;

re-computing the selected pre-computed travel recommendations by at least one of the processors based on the data obtained by the query;

in response to receiving the travel query, searching by at least one of the processors within the plurality of pre-computed travel recommendations in the fast access memory of the computer for travel recommendations that satisfy the parameters included in the travel query; and

issuing a response to the user by at least one of the one or more processors, the response including one or more of the pre-computed travel recommendations satisfying the parameters included in the travel query.

13. The method of claim 12 wherein the score indicative of the frequency with which the corresponding pre-computed recommendation is re-computed includes a value indicative of a popularity of the travel recommendation.

14. The method of claim 12 wherein launching the query in the plurality of travel databases and re-computing the selected pre-computed travel recommendations is done by a dedicated sub-system.

15. The method of claim 12 further comprising:

dividing the plurality of pre-computed travel recommendations into a plurality of homogeneous groups, each pre-computed travel recommendation in a homogeneous group having at least one parameter with the same value, and storing each group in one of a plurality of fast access memory locations.

16. The method of claim 12 wherein launching the query in the plurality of travel databases to obtain data relating to the selected pre-computed travel recommendations is done at a predetermined time interval.

17. The method of claim 12 wherein the query in the plurality of travel databases to obtain data relating to the selected pre-computed travel recommendations is done with a batch process.

18. The method of claim 12 further comprising:

indexing the plurality of pre-computed travel recommendations according to a multi-dimensional data structure.

19. The method of claim 12 further comprising:

in response to none of the pre-computed travel recommendations satisfying the parameters included in the travel query received from the user, searching within the plurality of pre-computed travel recommendations for travel recommendations that satisfy a travel query with relaxed constraints on one or more of the parameters included in the user travel query.

20. The method of claim 12 further comprising:

in response to none of the pre-computed travel recommendations satisfying the parameters included in the travel query received from the user, issuing an alert message to the user.

21. A data processing system comprising:

a processor; and

a memory coupled with the processor, the memory including instructions that, when executed by the processor, cause the processor to;

store a plurality of pre-computed travel recommendations in a fast access memory of the computer, each pre-computed travel recommendation comprising a price of the travel recommendation;

assign a score to each pre-computed travel recommendation, the score indicative of a frequency with which the corresponding pre-computed travel recommendation is re-computed;

select one or more of the plurality of pre-computed travel recommendations for recomputation based on the assigned scores;

launch a query in the plurality of travel databases to obtain data relating to the selected pre-computed travel recommendations;

re-compute the selected pre-computed travel recommendations based on the data obtained by the query;

determine a frequency with which the price of the selected pre-computed travel recommendations changes over a first span of dates including a punctual event;

determine the frequency with which the price of the selected pre-computed travel recommendations changes over a second span of dates not including the punctual event;

adjust the score of the selected pre-computed travel recommendations based on whether the current date falls in the first span or the second span of dates;

in response to receiving the travel query, search within the plurality of pre-computed travel recommendations in the fast access memory of the computer for travel recommendations that satisfy the parameters included in the travel query; and

issue a response to the user, the response including one or more of the pre-computed travel recommendations satisfying the parameters included in the travel query.

22. A computer program product comprising:

a non-transitory computer readable medium; and

program code stored on the computer readable storage medium that, when executed by a processor, causes the processor to;

store a plurality of pre-computed travel recommendations in a fast access memory of the computer, each pre-computed travel recommendation comprising a price of the travel recommendation;

assign a score to each pre-computed travel recommendation, wherein the score is indicative of a frequency with which the corresponding pre-computed travel recommendation is re-computed, and wherein the frequency with which the corresponding pre-computed travel recommendation is re-computed is based at least in part on a value indicative of a volatility of the price of the travel recommendation;

determine the volatility of the price of the corresponding pre-computed travel recommendation by comparing a price previously stored for the pre-computed travel recommendation to the price for the re-computed travel recommendation, and adjusting the volatility of the price of the corresponding pre-computed travel recommendation based on a difference between the stored and re-computed prices;

select one or more of the plurality of pre-computed travel recommendations for re-computing based on the assigned scores;

launch a query in the plurality of travel databases to obtain data relating to the selected pre-computed travel recommendations;

re-compute the selected pre-computed travel recommendations based on the data obtained by the query;

in response to receiving the travel query, search within the plurality of pre-computed travel recommendations in the fast access memory of the computer for travel recommendations that satisfy the parameters included in the travel query; and

issue a response to the user for the travel query, the response including the pre-computed travel recommendations satisfying the parameters included in the travel query.

23. A data processing system comprising:

a processor; and

a memory coupled with the processor, the memory including instructions that, when executed by the processor, cause the processor to;

store a plurality of pre-computed travel recommendations in a fast access memory of the computer, each pre-computed travel recommendation comprising a price of the travel recommendation;

assign a score to each pre-computed travel recommendation, wherein the score is indicative of a frequency with which the corresponding pre-computed travel recommendation is re-computed, and wherein the frequency with which the corresponding pre-computed travel recommendation is re-computed is based at least in part on a value indicative of a volatility of the price of the travel recommendation;

determine the volatility of the price of the corresponding pre-computed travel recommendation by comparing a price previously stored for the pre-computed travel recommendation to the price for the re-computed travel recommendation, and adjusting the volatility of the price of the corresponding pre-computed travel recommendation based on a difference between the stored and re-computed prices;

select one or more of the plurality of pre-computed travel recommendations for recomputation based on the assigned scores;

launch a query in the plurality of travel databases to obtain data relating to the selected pre-computed travel recommendations;

re-compute the selected pre-computed travel recommendations based on the data obtained by the query;

in response to receiving the travel query, search within the plurality of pre-computed travel recommendations in the fast access memory of the computer for travel recommendations that satisfy the parameters included in the travel query; and

issue a response to the user, the response including one or more of the pre-computed travel recommendations satisfying the parameters included in the travel query.