SYSTEM AND METHOD FOR FILTERING AND CREATING POINTS-OF-INTEREST

• US 20100198814A1
• Filed: 01/21/2010
• Published: 08/05/2010
• Est. Priority Date: 02/02/2009
• Status: Active Grant

• Current Assignee: Stripe, Inc.
• Original Assignee: Kota Enterprises, LLC (Concert Technology Corporation)
• Inventors: Jennings, Kenneth, Curtis, Scott, Petersen, Steven L.
• Granted Patent: US 10,530,654 B2
• Time in Patent Office: Days
• US Class Current: 707/722
• CPC Class Codes: G06F 21/6227 where protection concerns the structure of data, e.g. records, types, queries
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: H04L 41/0893 Assignment of logical groups to network elements
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04L 67/54 Presence management, e.g. monitoring or registration for receipt of user log-on information, or the connection status of the users
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/021 Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 64/00 Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

Systems and methods are provided for filtering and/or creating Points-of-Interest (POIs). In one embodiment, a list of POIs is obtained and then filtered based on crowd data related to the list of POIs to provide a filtered list of POIs. In another embodiment, one or more crowd-sourced POIs are created based on one or more crowds relevant to a corresponding bounding region for POI creation.

Claims

1. A method of operation of a computing device comprising:

obtaining a list of Points of Interest (POIs) including a plurality of POIs; and

filtering the list of POIs based on crowd data related to the list of POIs to provide a filtered list of POIs.

2. The method of claim 1 wherein filtering the list of POIs comprises filtering the list of POIs based on attributes of crowds relevant to the POIs in the list of POIs.

3. The method of claim 2 wherein filtering the list of POIs based on the attributes of the crowds at the plurality of POIs in the list of POIs comprises, for each POI of the plurality of POIs in the list of POIs:

identifying one or more crowds relevant to the POI;

determining whether the POI is to be filtered based on a comparison of one or more attributes of the one or more crowds and one or more crowd-based filtering criteria; and

excluding the POI from the filtered list of POIs if the POI is to be filtered.

4. The method of claim 3 wherein the one or more crowds relevant to the POI are one or more crowds located within a bounding region for the POI.

5. The method of claim 3 wherein the one or more crowds relevant to the POI are one or more crowds within a bounding region for the POI and one or more crowds intersecting the bounding region for the POI.

6. The method of claim 3 wherein for each crowd of the one or more crowds relevant to the POI, the one or more attributes of the crowd include at least one of a group consisting of:

a size of the crowd, an aggregate profile of the crowd, and a portion of an aggregate profile of the crowd.

7. The method of claim 3 wherein for each crowd of the one or more crowds relevant to the POI, the one or more attributes of the crowd include at least one of a group consisting of:

a degree of fragmentation of the crowd, a best-case average Degree of Separation (DOS) of the crowd, a best-case average DOS for one or more crowd fragments within the crowd, a worst-case average DOS of the crowd, a worst-case average DOS for one or more crowd fragments within the crowd, a degree of bidirectionality of friendships within the crowd, and a degree of bidirectionality of friendships within one or more crowd fragments within the crowd.

8. The method of claim 3 wherein the one or more crowd-based filtering criteria comprise one or more crowd-based filtering criteria that define one or more desired crowd attributes such that any POIs in the list of POIs that have the one or more desired crowd attributes are not filtered from the list of POIs.

9. The method of claim 3 wherein the one or more crowd-based filtering criteria comprise one or more crowd-based filtering criteria that define one or more non-desired crowd attributes such that any POIs in the list of POIs that have the one or more non-desired crowd attributes are filtered from the list of POIs.

10. The method of claim 1 wherein filtering the list of POIs comprises filtering the list of POIs based on aggregate profiles of crowds relevant to a bounding region for the list of POIs.

11. The method of claim 10 wherein the bounding region for the list of POIs is a geographic area encompassing the plurality of POIs in the list of POIs.

12. The method of claim 10 wherein filtering the list of POIs based on the aggregate profiles of the crowds relevant to the bounding region for the list of POIs comprises:

identifying the crowds relevant to the bounding region for the list of POIs;

obtaining aggregate profiles for the crowds relevant to the bounding region for the list of POIs, wherein each of the aggregate profiles is for one of the crowds relevant to the bounding region for the list of POIs;

combining the aggregate profiles to provide a combined aggregate profile for the crowds relevant to the bounding region for the list of POIs; and

filtering the list of POIs based on a comparison of at least a portion of the combined aggregate profile and metadata describing the plurality of POIs in the list of POIs.

13. The method of claim 12 wherein filtering the list of POIs based on the comparison of the at least a portion of the combined aggregate profile and the metadata describing the plurality of POIs in the list of POIs comprises, for each POI in the list of POIs:

determining whether the POI is to be filtered from the list of POIs based on a comparison of metadata describing the POI and the at least a portion of the combined aggregate profile; and

excluding the POI from the filtered list of POIs if the POI is to be filtered from the list of POIs.

14. The method of claim 12 wherein filtering the list of POIs based on the comparison of the at least a portion of the combined aggregate profile and the metadata describing the plurality of POIs in the list of POIs comprises:

identifying a dominant interest for the crowds relevant to the bounding region for the list of POIs from a plurality of interests included in the combined aggregate profile; and

for each POI in the list of POIs;

determining whether the POI is to be filtered from the list of POIs based on a comparison of metadata describing the POI and the dominant interest; and

excluding the POI from the filtered list of POIs if the POI is to be filtered from the list of POIs.

15. The method of claim 14 further comprising, if a dominant interest cannot be identified:

identifying one or more most significant interests for the crowds relevant to the bounding region for the list of POIs from the plurality of interests included in the combined aggregate profile; and

for each POI in the list of POIs;

determining whether the POI is to be filtered from the list of POIs based on a comparison of metadata describing the POI and the one or more most significant interests; and

excluding the POI from the filtered list of POIs if the POI is to be filtered from the list of POIs.

16. The method of claim 1 wherein the computing device is a server.

17. The method of claim 16 further comprising:

receiving a POI request from a requesting device via a network; and

determining a bounding region for the POI request,

wherein obtaining the list of POIs comprises obtaining a list of POIs located within the bounding region for the POI request.

18. The method of claim 17 wherein obtaining the list of POIs located within the bounding region for the POI request comprises obtaining the list of POIs located within the bounding region for the POI request from a local source of POIs.

19. The method of claim 17 wherein obtaining the list of POIs located within the bounding region for the POI request comprises obtaining the list of POIs located within the bounding region for the POI request from a remote third-party POI source.

20. The method of claim 17 further comprising returning the filtered list of POIs to the requesting device.

21. The method of claim 16 further comprising:

receiving the list of POIs from a requesting device via a network; and

returning the filtered list of POIs to the requesting device.

22. A server implemented as an article of manufacture, comprising:

a communication interface adapted to communicatively couple the server to a requesting device via a network; and

a controller associated with the communication interface and adapted to;

obtain a list of Points of Interest (POIs) including a plurality of POIs;

filter the list of POIs based on crowd data related to the list of POIs to provide a filtered list of POIs; and

return the filtered list of POIs to the requesting device.

23. A computer readable medium implemented as an article of manufacture and storing software for instructing a controller of a computing device to:

obtain a list of Points of Interest (POIs) including a plurality of POIs; and

filter the list of POIs based on crowd data related to the list of POIs to provide a filtered list of POIs.

24. A method of operation of a server comprising:

receiving a crowd-sourced Point of Interest (POI) request from a requesting device;

determining a bounding region for the crowd-sourced POI request;

identifying one or more crowds relevant to the bounding region for the crowd-sourced POI request;

creating one or more crowd-sourced POIs based on the one or more crowds relevant to the bounding region for the crowd-sourced POI request; and

returning the one or more crowd-sourced POIs to the requesting device.

25. The method of claim 24 wherein creating the one or more crowd-sourced POIs comprises creating a crowd-sourced POI for each of the one or more crowds relevant to the bounding region for the crowd-sourced POI request.

26. The method of claim 24 wherein creating the one or more crowd-sourced POIs comprises:

creating a crowd-sourced POI for each of the one or more crowds relevant to the bounding region for the crowd-sourced POI request to provide one or more initial crowd-sourced POIs; and

processing the one or more initial crowd-sourced POIs to provide the one or more crowd-sourced POIs, wherein processing the one or more initial crowd-sourced POIs comprises combining ones of the one or more initial crowd-sourced POIs that are within a predefined distance from one another.

27. The method of claim 24 wherein creating the one or more crowd-sourced POIs comprises:

processing the one or more crowds relevant to the bounding region for the crowd-sourced POI request to provide one or more resulting crowds, wherein processing the one or more crowds comprises combining ones of the one or more crowds that are within a predefined distance from one another; and

creating a crowd-sourced POI for each of the one or more resulting crowds to provide the one or more crowd-sourced POIs.

28. The method of claim 24 wherein creating the one or more crowd-sourced POIs comprises, for each crowd-sourced POI of the one or more crowd-sourced POIs, generating metadata describing the crowd-sourced POI based on one or more crowds relevant to a bounding region for the crowd-sourced POI.

29. The method of claim 28 further comprising, for each crowd-sourced POI of at least one of the one or more crowd-sourced POIs, augmenting the metadata describing the crowd-sourced POI based on historical data regarding interests of users previously located within the bounding region for the crowd-sourced POI.

30. The method of claim 28 further comprising, for each crowd-sourced POI of at least one of the one or more crowd-sourced POIs, augmenting the metadata describing the crowd-sourced POI based on historical data regarding interests of crowds previously located within the bounding region for the crowd-sourced POI.

31. The method of claim 24 further comprising:

determining whether a crowd-sourced POI of the one or more crowd-sourced POIs is to be promoted to permanent POI; and

promoting the crowd-sourced POI to a permanent POI if the crowd-sourced POI is to be promoted to a permanent POI.