Location based profiling

• US 20020111172A1
• Filed: 02/14/2001
• Published: 08/15/2002
• Est. Priority Date: 02/14/2001
• Status: Abandoned Application

• Current Assignee: Prime Research Alliance E, LLC
• Original Assignee: Prime Research Alliance E, LLC
• Inventors: Eldering, Charles A., Ryder, Douglas J., DeWolf, Frederik M.
• Application Number:
  US09/782,962
• Publication Number:
  US 20020111172A1
• Time in Patent Office: Days
• US Class Current: 455/456.3
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 8/18 Processing of user or subscriber data, e.g. subscribed services, user preferences or user profiles; Transfer of user or subscriber data

Abstract

A method and system for profiling a subscriber based on location. A subscriber'"'"'s daily activities and locations traveled while partaking in the activities are observed and a psychodemographic profile is developed from the subscriber'"'"'s pattern of activities. The pattern of activities is associated with a time and a frequency component that is then used to predict a subscriber'"'"'s activity.

Claims

1. A method for generating a profile of a subscriber by monitoring locations traveled by the subscriber, the method comprising:

receiving subscriber location data, wherein the subscriber location data identifies locations the subscriber has traveled;

retrieving location characteristics for the locations the subscriber has traveled; and

generating the profile based upon the subscriber location data and the location characteristics.

2. The method of claim 1, wherein the location characteristics include a description of the locations the subscriber has traveled.

3. The method of claim 1, wherein the location characteristics include establishments within the location.

4. The method of claim 3, further comprising retrieving a set of heuristic rules associated with the establishments, wherein said generating the profile includes generating the profile based on the subscriber location data, the location characteristics, and the s et of heuristic rules.

5. The method of claim 1, further comprising retrieving a set of heuristic rules associated with the locations the subscriber has traveled, wherein said generating the profile includes generating the profile based on the subscriber location data, the location characteristics, and the set of heuristic rules.

6. The method of claim 1, wherein the subscriber location data includes locations the subscriber has traveled and an associated time.

7. The method of claim 6, further comprising:

aggregating the subscriber location data by time;

analyzing the aggregated subscriber location data to identify trends; and

associating the trends with predicted activities.

8. The method of claim 7, further comprising associating a predicted route with each of the predicted activities.

9. The method of claim 7, wherein the predicted activities are a probabilistic measure of the likelihood of the subscriber partaking in particular activities.

10. The method of claim 8, wherein the predicted route is a probabilistic measure of the likelihood of the subscriber taking a particular route.

11. The method of claim 1, wherein said receiving subscriber location data includes receiving subscriber location from a wireless device.

12. The method of claim 1, wherein said receiving subscriber location data includes receiving subscriber location from a wireless network.

13. The method of claim 1, wherein a location of the subscriber is determined by a wireless network determining a location of a wireless device the subscriber has.

14. The method of claim 1, wherein a location of the subscriber is determined by a GPS chipset with in a wireless device the subscriber has receiving location coordinates from a GPS system.

16. The method of claim 15, wherein the subscriber has a wireless device that is capable of generating location data.

18. The method of claim 17, the subscribers have wireless devices capable of generating location data.

15. A method for predicting an activity of a subscriber, the method comprising:

receiving subscriber location data associated with where the subscriber has traveled, wherein the subscriber location data includes location and time;

aggregating the subscriber location data;

analyzing the aggregated subscriber location data to identify trends; and

associating the trends with predicted activities.

17. A method for profiling a location based on subscribers that travel to the location, the method comprising:

monitoring subscribers who travel to the location;

receiving a subscriber profile for each subscriber that travels to the location;

aggregating the subscriber profiles to generate a location profile.