User Description Based on Contexts of Location and Time

• US 20130267249A1
• Filed: 06/05/2012
• Published: 10/10/2013
• Est. Priority Date: 04/10/2012
• Status: Active Grant

• Current Assignee: Verve Group, Inc. (Samarion SE)
• Original Assignee: Sense Networks, Inc. (Samarion SE)
• Inventors: Rosenberg, David
• Granted Patent: US 8,849,312 B2
• Time in Patent Office: Days
• US Class Current: 455/456.3
• CPC Class Codes: G06F 21/316 by observing the pattern of computer usage, e.g. typical user behaviour
• CPC Class Codes: G06F 2221/2111 Location-sensitive, e.g. geographical location, GPS
• 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: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 4/21 for social networking applications

Abstract

A description of a user is estimated based on the context of a user'"'"'s past and present locations. A disclosed data-processing system continually receives data points for each user that represent spatial and/or temporal events. These events represent, for example, presence of a person at a specific geographic location such as a geographic area or point of interest (POI). The data-processing system evaluates the received data points in relation to one or more of the geographic locations, yielding results that are also based on the demographic characteristics of each visited location and the commercial characteristics of each visited location. The data-processing system evaluates the data points also to determine patterns exhibited in each user'"'"'s activity or inactivity, and patterns exhibited in the distance traveled and the type of travel. The data-processing system bases the user descriptions on the results of these evaluations.

Claims

1-20. -20. (canceled)

21. A method comprising:

receiving, by a data-processing system, a plurality of data points D that correspond to a first user, wherein each of the data points in the plurality represents at least one of i) a spatial event and ii) a temporal event, and wherein the plurality comprises at least i) a first data point that occurs at a first time t₁, d(t₁), and ii) a second data point that occurs at a second time t₂, d(t₂);

determining a difference in time between a first time that is represented by the first data point d(t₁) and a second time that is represented by the second data point d(t₂);

evaluating

i) a first characteristic c₁ for a first geographic location I₁, yielding a first value c₁(I₁), and

ii) the first data point d(t₁) in relation to the first geographic location I₁, yielding a first result that is based on the first value c₁(I₁); and

estimating a description of the first user, wherein the description is based on i) the determined difference in time and ii) the first result.

22. The method of claim 21 wherein the first geographic location I₁ is a geographic area.

23. The method of claim 21 wherein the first geographic location I₁ is a geographic point of interest.

24. The method of claim 23 wherein evaluating the first data point d(t₁) comprises determining proximity of a geolocation represented by d(t₁) to the geographic point of interest represented by the first geographic location I₁.

25. The method of claim 21 further comprising assessing inactivity of the first user based on the difference in time between d(t₁) and d(t₂), wherein d(t₁) and d(t₂) represent a pair of consecutive events and wherein the description of the first user is based also on the inactivity.

26. The method of claim 25 wherein assessing inactivity comprises assigning the pair of consecutive events to a predetermined bin.

27. The method of claim 26 wherein the predetermined bin is one of a plurality of bins for tracking user inactivity.

28. The method of claim 21 further comprising:

determining a difference in geolocation between a first geolocation that is represented by the first data point d(t₁) and a second geolocation that is represented by the second data point d(t₂);

wherein the description of the first user is also based on the determined difference in geolocation.

29. The method of claim 28 further comprising assessing distance traveled of the first user based on the difference in geolocation between d(t₁) and d(t₂), wherein the description of the first user is based also on the distance traveled.

30. The method of claim 29 wherein d(t₁) and d(t₂) represent a pair of consecutive events.

31. A method comprising:

receiving, by a data-processing system, a plurality of data points D that correspond to a first user, wherein each of the data points in the plurality represents at least one of i) a spatial event and ii) a temporal event, and wherein the plurality comprises at least i) a first data point that occurs at a first time t₁, d(t_l), and ii) a second data point that occurs at a second time t₂, d(t₂);

determining a difference in geolocation between a first geolocation that is represented by the first data point d(t₁) and a second geolocation that is represented by the second data point d(t₂);

evaluating

i) a first characteristic c₁ for a first geographic location I₁, yielding a first value c₁(I₁), and

ii) the first data point d(t₁) in relation to the first geographic location I_i, yielding a first result that is based on the first value c₁(I₁); and

estimating a description of the first user, wherein the description is based on i) the determined difference in geolocation and ii) the first result.

32. The method of claim 31 wherein the first geographic location I₁ is a geographic area.

33. The method of claim 31 wherein the first geographic location I₁ is a geographic point of interest.

34. The method of claim 33 wherein evaluating the first data point d(t₁) comprises determining proximity of the first geolocation represented by d(t₁), to the geographic point of interest represented by the first geographic location I₁.

35. The method of claim 34 wherein determining the proximity to the geographic point of interest comprises weighting the distances of the first geolocation to multiple points of interest.

36. The method of claim 31 further comprising assessing distance traveled of the first user based on the difference in geolocation between d(t₁) and d(t₂), wherein the description of the first user is based also on the distance traveled.

37. The method of claim 36 wherein wherein d(t₁) and d(t₂) represent a first pair of consecutive events.

38. The method of claim 37 wherein assessing the distance traveled comprises summing i) the difference in geolocation of the first pair of consecutive events and ii) a difference in geolocation of a second pair of consecutive events, wherein d(t₂) is also an event in the second pair.

39. The method of claim 36 wherein the description of the first user is also based on time of day.

40. A method comprising:

receiving, by a data-processing system, a plurality of data points D that correspond to a first user, wherein each of the data points in the plurality represents at least one of i) a spatial event and ii) a temporal event, and wherein the plurality comprises at least i) a first data point that occurs at a first time t₁, d(t₁), and ii) a second data point that occurs at a second time t₂, d(t₂);

determining a level of entropy of the plurality of data points D, wherein the level of entropy characterizes a randomness of the plurality;

evaluating

i) a first characteristic c₁ for a first geographic location I₁, yielding a first value c₁(I₁), and

ii) the first data point d(t₁) in relation to the first geographic location I₁, yielding a first result that is based on the first value c₁(I₁); and

estimating a description of the first user, wherein the description is based on i) the determined level of entropy and ii) the first result.

41. The method of claim 40 wherein the first geographic location I₁ is a geographic area.

42. The method of claim 40 wherein the first geographic location I₁ is a geographic point of interest.

43. The method of claim 42 wherein evaluating the first data point d(t₁) comprises determining proximity of a geolocation represented by d(t₁) to the geographic point of interest represented by the first geographic location I₁.

44. The method of claim 40 wherein determining the level of entropy comprises determining whether the first data point d(t₁) and the second data point d(t₂) correspond to different places visited by the first user.

45. The method of claim 44 wherein determining the level of entropy further comprises tracking the number of places visited by the first user.

46. The method of claim 40 further comprising assessing inactivity of the first user based on the difference in time between d(t₁) and d(t₂), wherein d(t₁) and d(t₂) represent a pair of consecutive events, and wherein the description of the first user is based also on the inactivity.

47. The method of claim 46 wherein assessing inactivity comprises assigning the pair of consecutive events to a predetermined bin.

48. The method of claim 47 wherein the predetermined bin is one of a plurality of bins for tracking user inactivity.