SYSTEM AND METHOD FOR ORGANIZING HOTEL-RELATED DATA

• US 20090287546A1
• Filed: 05/13/2009
• Published: 11/19/2009
• Est. Priority Date: 05/16/2008
• Status: Abandoned Application

• Current Assignee: Concur Technologies Incorporated (SAP SE)
• Original Assignee: TRX, Inc. (SAP SE)
• Inventors: Tomosky, Thomas K., Gillespie, Scott
• Application Number:
  US12/465,067
• Publication Number:
  US 20090287546A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06Q 10/02 Reservations, e.g. for tickets, services or events
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 50/12 Hotels or restaurants

Abstract

A method for grouping hotels for a travel entity may include identifying a plurality of hotels stayed at in the past by members of a travel entity, identifying a subset of hotels having a particular significance to the travel entity, each hotel being associated with a position indicator, clustering hotels in the subset of hotels using a clustering algorithm, where the position indicator for each hotel serves as the basis for calculating a geographical similarity measure for the clustering algorithm, identifying hotels not used by the travel entity but that are within the boundaries of the clusters, and optionally displaying a visual depiction of a cluster of hotels.

Claims

1. A method for grouping hotels for a travel entity, comprising:

identifying a plurality of hotels stayed at in the past by members of a travel entity;

identifying a subset of hotels having a particular significance to the travel entity, each hotel being associated with a position indicator;

clustering hotels in the subset of hotels using a clustering algorithm implemented by one or more processors, where the position indicator for each hotel serves as a basis for a geographic similarity measure for the clustering algorithm; and

displaying on a display device a visual depiction of hotels in a given cluster resulting from the clustering algorithm.

2. The method of claim 1 further comprising analyzing hotels associated with the given cluster.

3. The method of claim 2 further comprises determining a statistic for the given cluster selected from a group consisting of a market share, a compliance percentage, a coverage percentage, a support ratio and an overlap.

4. The method of claim 1, wherein the step of identifying a subset of hotels having a particular significance to the travel entity includes identifying the subset of hotels as preferred hotels.

5. The method of claim 1, wherein the step of identifying a subset of hotels having a particular significance to the travel entity includes identifying the hotels at which members of the travel entity have stayed for a predetermined number of room-nights or have spent a minimum amount of money.

6. The method of claim 1, further comprising determining a centroid of the cluster of hotels based on the position indicators of the hotels.

7. The method of claim 1, further comprising determining a weighted centroid of the cluster of hotels based on the position indicators of the hotels and a weighting metric.

8. The method of claim 1, wherein the step of displaying a visual depiction of a cluster of hotels includes generating a map of a geographical area, plotting each of the hotels in the cluster of hotels on the map, and displaying the map and the hotels plotted thereon.

9. The method of claim 8, further comprising filtering the hotels plotted on the map according to a predetermined criterion.

10. The method of claim 9, wherein the predetermined criterion is a quality rating of the hotels.

11. A method for grouping hotels for a travel entity, comprising:

identifying a plurality of hotels having a particular significance to a travel entity, each hotel being associated with a position indicator;

clustering hotels in the plurality of hotels using a clustering algorithm implemented by one or more processors, where the position indicator for each hotel serves as a distance measure for the clustering algorithm;

for a given cluster, defining a geographic area that includes hotels within the given cluster;

determining hotels within the geographic area including one or more hotels exclusive from the plurality of hotels; and

visually depicting on a display device the hotels within the geographic area.

12. The method of claim 11 further comprising analyzing at least one of the hotels associated with the given cluster.

13. The method of claim 12 further comprises determining a statistic for the given cluster selected from a group consisting of a market share, a compliance percentage, a coverage percentage, a support ratio and an overlap.

14. The method of claim 11, wherein the step of identifying a plurality of hotels having a particular significance to a travel entity includes identifying the plurality of hotels as preferred hotels.

15. The method of claim 11, wherein the step of identifying a plurality of hotels having a particular significance to the travel entity includes identifying the hotels at which members of the travel entity have stayed for a predetermined number of room-nights.

16. The method of claim 11, further comprising determining a centroid of the cluster of hotels based on the position indicators of the plurality of hotels.

17. The method of claim 11, further comprising determining a weighted centroid of the cluster of hotels based on the position indicators of the hotels and a weighting metric.

18. The method of claim 11, wherein the step of visually depicting the hotels includes generating a map of the geographical area, plotting each of the hotels in the cluster of hotels on the map, and displaying the map and the hotels plotted thereon.

19. The method of claim 18, further comprising filtering the hotels plotted on the map according to a predetermined criterion.

20. The method of claim 19, wherein the predetermined criterion is a quality rating of the hotels.