DETERMINING DEMOGRAPHIC DATA

• US 20150006255A1
• Filed: 06/28/2013
• Published: 01/01/2015
• Est. Priority Date: 06/28/2013
• Status: Abandoned Application

• Current Assignee: StreetLight Data Incorporated (Jacobs Solutions, Inc.)
• Original Assignee: StreetLight Data Incorporated (Jacobs Solutions, Inc.)
• Inventors: Schewel, Laura, Friedman, Paul
• Application Number:
  US13/931,173
• Publication Number:
  US 20150006255A1
• Time in Patent Office: Days
• US Class Current: 705/7.34
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration
• CPC Class Codes: H04W 4/00 Services specially adapted for wireless communication networks; Facilities therefor
• CPC Class Codes: H04W 4/02 Services making use of location information

Abstract

A system for determining a demographic data comprises an input interface configured to receive a location data of a device or group of devices, a processor configured to determine a user characterization data associated with the device or group of devices and to determine a probability that the device or group of devices is associated with a location of interest, and an output interface configured to provide an aggregated characterization data associated with the location of interest.

Claims

1. A system for determining a demographic data, comprising:

an input interface configured to;

receive a location data of a device;

a processor configured to;

determine a user characterization data associated with the device; and

determine a probability that the device is associated with a location of interest; and

an output interface configured to;

provide an aggregated characterization data associated with the location of interest.

2. The system of claim 1, wherein the device is one of a plurality of devices and the aggregated characterization data is aggregated from the plurality of devices.

3. The system of claim 2, wherein the aggregated characterization data comprises an is accumulation of products.

4. The system of claim 3, wherein each product of the accumulation of products comprises the product of a probability that one of the plurality of devices is associated with the location of interest with the user characterization data associated with the one of the plurality of devices.

5. The system of claim 1, wherein the probability that the device is associated with the location of interest comprises the likelihood that the device was near the location of interest.

6. The system of claim 1, wherein the probability that the device is associated with the location of interest comprises the likelihood that the device passed within a threshold distance of the location of interest.

7. The system of claim 1, wherein the location data comprises a location probability distribution.

8. The system of claim 7, wherein the location probability distribution comprises a maximum likelihood point and a radius.

9. The system of claim 1, wherein the location data comprises a location time.

10. The system of claim 1, wherein the user characterization data comprises a demographic probability distribution.

11. The system of claim 10, wherein the demographic probability distribution comprises census data.

12. The system of claim 11, wherein the census data comprises one or more of the following:

age data, income data, ethnicity data, gender data, employment data, education, household composition, political preferences, buying habits, immigration, language spoken at home, or family status data.

13. The system of claim 10, wherein the demographic probability distribution comprises user type data.

14. The system of claim 13, wherein the user type data comprises one or more of the following:

heavy shopper data, stay at home parent data, commuter data, shopper with disposable income data, college student data, work location/commute habits, other mobility patterns, shopping patterns/favorite places, response of user behavior to external events, response or user is behavior to weather, response or user behavior to gas prices, response or user behavior to economic factors, or gender data.

15. A system as in claim 1, wherein the user characterization data comprises an associated location.

16. A system as in claim 15, wherein the associated location comprises one or more of the following:

a specific retail location, a recreation location, a school, or a religious establishment.

17. A system as in claim 1, wherein the user characterization data comprises a visit frequency.

18. A system as in claim 1, wherein the user characterization data comprises a visit unusualness.

19. A system as in claim 1, wherein the user characterization data comprises trip type.

20. A system as in claim 1, wherein the user characterization data comprises another establishments along the route recently.

21. A system as in claim 1, wherein the user characterization data comprises a preceding action.

22. A system as in claim 21, wherein the preceding action comprises a preceding location visited.

23. A system as in claim 21, wherein the preceding action comprises one or more of the following:

leaving home, leaving school, shopping, exercise, running an errand, having lunch, having a meal, or having dinner.

24. A system as in claim 1, wherein the user characterization data comprises a following action.

25. A system as in claim 24, wherein the following action comprises a following location visited.

26. A system as in claim 24, wherein the following action comprises one or more of the following:

arriving home, arriving at school, shopping, exercise, having lunch, or having dinner.

27. The system of claim 1, wherein the aggregated data is a function of time.

28. The system of claim 27, wherein the aggregated data time dependency comprises a is dependency on one or more of the following:

hour, day, year, month, type of hour, type of day, or type of month.

29. The system of claim 1, wherein the processor is further configured to determine a set of one or more locations associated with the device.

30. The system of claim 29, wherein the set of one or more locations associated with the device comprises a home location.

31. The system of claim 29, wherein the set of one or more locations associated with the device comprises a work location.

32. The system of claim 29, wherein the set of one or more locations associated with the device comprises one of the following:

a school location, a shopping location, a work-place location, a recreational location, a tourist location, a frequently-visited friend'"'"'s home location, or an exercise location.

33. The system of claim 29, wherein the user characterization data is based on one of the set of one or more locations associated with the device.

34. The system of claim 1, wherein the aggregated data comprises a home location probability distribution.

35. The system of claim 1, wherein the aggregated data comprises a work location probability distribution.

36. The system of claim 1, wherein the aggregated data comprises a demographic data probability distribution.

37. The system of claim 36, wherein the demographic data probability distribution comprises a probability distribution of one or more of the following:

census data, age data, income data, ethnicity data, gender data, user type data, heavy shopper data, stay-at-home parent data, to commuter data, shopper with disposable income data, college student data, associated location data, visit frequency data, visit unusualness data, trip type data, competing establishments seen recently data, preceding action data, or following action data.

38. A method for determining a demographic data, comprising:

receiving a location data of a device;

determining, using a processor;

a user characterization data associated with the device; and

a probability that the device is associated with a location of interest; and

providing an aggregated characterization data associated with the location of interest.

39. A computer program product for determining a demographic data, the computer program product being embodied in a tangible computer readable storage medium and comprising computer instructions for:

receiving a location data of a device;

determining, using a processor;

a user characterization data associated with the device; and

a probability that the device is associated with a location of interest; and

providing an aggregated characterization data associated with the location of interest.