Predicting the activities of an individual or group using minimal information

• US 7,822,843 B2
• Filed: 08/13/2001
• Issued: 10/26/2010
• Est. Priority Date: 08/13/2001
• Status: Expired due to Term

• Current Assignee: Cox Communications Incorporated (Cox Enterprises Incorporated)
• Original Assignee: Cox Communications Incorporated (Cox Enterprises Incorporated)
• Inventors: Perdon, Albert Honey, Oddo, Anthony Scott
• Primary Examiner(s): Etienne; Ario
• Assistant Examiner(s): SALL, EL HADJI MALICK
• Application Number:
  US09/928,493
• Publication Number:
  US 20030033405A1
• Time in Patent Office: 3,361 Days
• Field of Search: 709/224, 709/219, 707/10, 710/10
• US Class Current: 709/224
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: H04L 67/306 User profiles
• 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 69/329 in the application layer [OSI layer 7]
• CPC Class Codes: H04L 9/40 Network security protocols

Abstract

A method and system are provided for predicting the behavior of an individual, e.g., one engaged in an on-line session, based on a comparison of the individual'"'"'s activities during that session with those participated in by multiple other parties. The individual'"'"'s activities during the session and certain attendant conditions are monitored and compared with a continually updated database that reflects (a) the cumulative activities of all other parties and their attendant conditions and (b) behavioral trends exhibited by those other parties based on their participation in various types of activities under various conditions. When similarities are detected between the individual'"'"'s activities and their attendant conditions and those of certain other parties, the corresponding behavioral trend of those other parties is attributed to the individual. The method and system are implemented in connection with an interactive service, for example, in an Internet environment, wherein the prediction of behavior involves identifying web sites that are likely to be visited by the individual. This prediction can be used to initiate the delivery of informational content targeted to that individual.

Claims

1. A method for predicting the behavior of a current user of an interactive television service, the method comprising:

observing activity associated with a set top box of a current user engaging with the interactive television service;

collecting the observed activity in a database;

identifying, by the set top box, activities of the current user engaging with the interactive television service and conditions surrounding each of the identified activities of the current user, including amount of time the current user participated in each of the identified activities;

accessing a first collection of data comprising data associated with;

(i) cumulative activities associated with a set top box of other users,

(ii) conditions surrounding the cumulative activities associated with a set top box of the other users, including amount of time that each other user participated in each respective activity, and

(iii) patterns of behavior associated with the cumulative activities associated with a set top box of the other users and the conditions surrounding the cumulative activities associated with a set top box of the other users, wherein the cumulative activities include viewing interactive television programming;

comparing the identified activities and the surrounding conditions associated with the identified activities of the current user with the cumulative activities and the surrounding conditions associated with the cumulative activities of the other users to identify similarities therebetween;

identifying a pattern of behavior associated with the identified similarities between the identified activities and the surrounding conditions associated with the identified activities of the current user and the cumulative activities and the surrounding conditions associated with the cumulative activities of the other users; and

attributing to the current user the identified pattern of behavior as a future behavior of the current user.

2. The method of claim 1, wherein the identifying step further comprises identifying personal attributes of the current user;

the first collection of data further comprises data associated with personal attributes of the other users; and

the comparing step further comprises comparing the personal attributes of the current user with the personal attributes of the other users to identify the similarities.

3. The method of claim 1, wherein the first collection of data is based on activities the other users participated while engaged with the interactive television service.

4. The method of claim 1, wherein the other users are unrelated individual persons.

5. The method of claim 1, wherein the other users are members of a group and the current user is identifiable as a potential member of that group.

6. The method of claim 1, further comprising the step of:

periodically updating the first collection of data to reflect the other users'"'"' ongoing participation in additional activities.

7. The method of claim 6, wherein the step of periodically updating occurs in real time, during the current user'"'"'s engagement with the interactive television service.

8. The method of claim 1, further comprising:

accessing a second collection of data comprising data associated with;

(i) A plurality of activities available via the interactive television service and

(ii) information about each of the plurality of available activities distinguishing the activity from others of the plurality of the available activities,

wherein the step of attributing includes selecting, from the plurality of available activities and based on the second collection of data, one or more activities in which the current user is most likely to participate during the engagement with the interactive television service.

9. The method of claim 1, wherein:

the interactive television service is accessed through the Internet,

the activities of the current user and the cumulative activities of the other users include visits to Internet web sites, and

the first collection of data further comprises data associated with;

(i) An identity of each other user,

(ii) types of Internet web sites that each other user has visited,

(iii) content of each type of Internet web site visited by each other user, and

(iv) Amount of time spent at each type of internet web site by each other user.

10. The method of claim 9, further comprising the step of:

periodically updating the first collection of data to reflect the other users'"'"' visits to additional Internet web sites.

11. The method of claim 10, wherein the step of periodically updating occurs in real time, during the current user'"'"'s engagement with the interactive television service.

12. The method of claim 9, further comprising:

accessing a second collection of data comprising data associated with;

(i) A plurality of types of Internet web sites available for the current user to visit and

(ii) information about each type of the plurality of types of Internet web sites distinguishing the type from others of the plurality of types of Internet web sites,

wherein the step of attributing includes selecting, from the plurality of Internet web sites, one or more types of Internet web sites which the current user is most likely to visit during the engagement with the interactive television service.

13. A method for predicting the behavior of a user of an interactive television service, during a particular period of engagement with the interactive television service, the method comprising:

observing activity associated with a set top box of a user engaging with the interactive television service;

collecting the observed activity in a database;

identifying, by the set top box, activities in which the user participates during the period of engagement and conditions surrounding each of the identified activities of the user, including amount of time the current user participated in each of the identified activities;

identifying activities associated with a set top box of multiple other contemporaneous users of the interactive television service during the period of engagement and conditions surrounding the identified activities associated with the set top box of the other contemporaneous users, including amount of time that each other user participated in each respective activity, wherein the activities associated with the set top box of the other contemporaneous users include viewing interactive television programming;

maintaining a first collection of data comprising data associated with cumulative activities and surrounding conditions associated with the set top box of the user collected in the database and data associated with the set top box of the other contemporaneous users identified during the period of engagement;

determining, based on the first collection of data, patterns of behavior associated with the cumulative activities associated with a set top box of the other contemporaneous users and the conditions surrounding the cumulative activities associated with a set top box of the other contemporaneous users during the period of engagement;

incorporating into the first collection of data, data associated with the determined patterns of behavior;

comparing (i) The present activities and the surrounding conditions associated with the present activities of the user and (ii) The cumulative activities and the surrounding conditions associated with the cumulative activities of the other contemporaneous users to identify similarities therebetween;

identifying a pattern of behavior associated with the identified similarities between the present activities and the surrounding conditions associated with the present activities of the current user and the cumulative activities and the surrounding conditions associated with the cumulative activities of the other contemporaneous users; and

attributing to the user the identified pattern of behavior as a future behavior of the current user.

14. The method of claim 13, further comprising:

continually updating the first collection of data to reflect participation of the user and the other contemporaneous users in additional activities and new patterns of behavior determined based on the participation of the user and the other contemporaneous users in additional activities,

wherein the steps of comparing and attributing are performed, at any given point in time, using the updated first collection of data.

15. The method of claim 14, further comprising:

accessing a second collection of data comprising data associated with;

(i) A plurality of activities that are available via the interactive television service and

(ii) information about each of the plurality of available activities distinguishing the activity from others of the plurality of available activities,

wherein the step of attributing further comprises selecting one or more of the plurality of available activities in which the user is most likely to participate during the period of engagement with the interactive television service.

16. The method of claim 14, wherein:

the interactive television service is accessed through the Internet,

the user and other contemporaneous users activities include visits to Internet web sites, and

the first collection of data includes data associated with

(i) types of Internet web sites that the user and the other contemporaneous users have visited,

(ii) content of each type of Internet web site visited, and

(iii) Amount of time spent at each type of Internet web site visited.

17. The method of claim 16, further comprising:

accessing a second collection of data comprising data associated with;

(i) A plurality of types of Internet web sites available for the user to visit and

(ii) information about each of the plurality of types distinguishing the type from others of the plurality of types,

wherein the step of attributing further comprises one or more of the plurality of types of web sites, which the current user is most likely to visit during the engagement with the interactive television service.

18. The method of claim 13, wherein the other users are members of a group and the current user is identifiable as a potential member of that group.

19. The method of claim 13, further comprising the step of:

periodically updating the first collection of data to reflect the other users'"'"' ongoing participation in additional activities.

20. The method of claim 19, wherein the step of periodically updating occurs in real time, during the current user'"'"'s engagement with the interactive television service.

21. The method of claim 13, wherein:

the interactive television service is accessed through the Internet,

the activities of the current user and the cumulative activities of the other users include visits to Internet web sites, and

the first collection of data further comprises data associated with;

(i) An identity of each other user,

(ii) types of Internet web sites that each other user has visited,

(iii) content of each type of Internet web site visited by each other user, and

(iv) Amount of time spent at each type of Internet web site by each other user.

22. A non-transitory computer-readable medium having stored thereon instructions for predicting the behavior of a current user of an interactive television service which, when executed by a processor, cause the processor to perform the steps of:

observing activity associated with a set top box of a current user engaging with the interactive television service;

collecting the observed activity in a database;

identifying, by the set top box, activities of the current user engaging with the interactive television service and conditions surrounding each of the identified activities of the current user, including amount of time the current user participated in each of the identified activities;

accessing a first collection of data comprising data associated with;

(i) cumulative activities associated with a set top box of other users,

(ii) conditions surrounding the cumulative activities associated with a set top box of the other users, including amount of time that each other user participated in each respective activity, and

(iii) patterns of behavior associated with the cumulative activities associated with a set top box of the other users and the conditions surrounding the cumulative activities associated with a set top box of the other users, wherein the cumulative activities include viewing interactive television programming;

comparing the identified activities and the surrounding conditions associated with the identified activities of the current user with the cumulative activities and the surrounding conditions associated with the cumulative activities of the other users to identify similarities therebetween;

identifying a pattern of behavior associated with the identified similarities between the identified activities and the surrounding conditions associated with the identified activities of the current user and the cumulative activities and the surrounding conditions associated with the cumulative activities of the other users; and

attributing to the current user the identified pattern of behavior as a future behavior of the current user.

23. The non-transitory computer-readable medium of claim 22, wherein the identifying step further comprises identifying personal attributes of the current user;

the first collection of data further comprises data associated with personal attributes of the other users; and

the comparing step further comprises comparing the personal attributes of the current user with the personal attributes of the other users to identify the similarities.

24. The non-transitory computer-readable medium of claim 22, wherein the first collection of data is based on activities the other users participated while engaged with the interactive television service.

25. The non-transitory computer-readable medium of claim 22, having stored thereon further instructions which, when executed by the processor, cause the processor to perform the step of:

periodically updating the first collection of data to reflect the other users'"'"' ongoing participation in additional activities.

26. The non-transitory computer-readable medium of claim 25, wherein the instructions that cause the processor to perform the step of periodically updating cause it to do so in real time, during the current user'"'"'s engagement with the interactive television service.

27. The non-transitory computer-readable medium of claim 22, having stored thereon further instructions which, when executed by the processor, cause the processor to perform the step of:

accessing a second collection of data comprising data associated with;

(i) A plurality of activities that are available via the interactive television service and

(ii) information about each of the plurality of available activities distinguishing the activity from others of the plurality of the available activities,

wherein the step of attributing includes selecting, from the plurality of available activities and based on the second collection of data, one or more activities in which the current user is most likely to participate during the engagement with the interactive television service.

28. The non-transitory computer-readable medium of claim 22, wherein:

the interactive television service is accessed through the Internet,

the activities of the current user m and the cumulative activities of the other users include visits to Internet web sites, and

the first collection of data further comprises data associated with;

(i) An identity of each other user,

(ii) types of Internet web sites that each other user has visited,

(iii) content of each type of Internet web site visited by each other user, and

(iv) Amount of time spent at each type of Internet web site by each other user.

29. An apparatus for predicting the behavior of a current user of an interactive television service, comprising:

means for observing activity associated with a set top box of a current user engaging with the interactive television service;

means for collecting the observed activity in a database;

means for identifying activities of the current user engaging with the interactive television service and conditions surrounding each of the identified activities, including amount of time the current user participated in each of the identified activities;

means for accessing a first collection of data comprising data associated with;

(i) cumulative activities associated with a set top box of other users,

(ii) conditions surrounding the cumulative activities associated with a set top box of the other users, including amount of time that each other user participated in each respective activity, and

(iii) patterns of behavior associated with the cumulative activities associated with a set top box of the other users and the conditions surrounding the cumulative activities associated with a set top box of the other users, wherein the cumulative activities include viewing interactive television programming;

means for comparing the identified activities and the surrounding conditions associated with the identified activities of the current user with the cumulative activities and the surrounding conditions associated with the cumulative activities of the other users to identify similarities therebetween;

means for identifying a pattern of behavior associated with the identified similarities between the identified activities and the surrounding conditions associated with the identified activities of the current user and the cumulative activities and the surrounding conditions associated with the cumulative activities of the other users; and

means for attributing to the current user the identified pattern of behavior as a future behavior of the current user.

30. The apparatus of claim 29, wherein:

the means for identifying the conditions surrounding each of the identified activities further comprises means for identifying personal attributes of the current user;

the first collection of data further comprises data associated with personal attributes of the other users; and

means for comparing further comprises means for comparing the personal attributes of the current user with the personal attributes of the other users to identify the similarities.

31. The apparatus of claim 29, wherein the first collection of data is based on activities the other users participated while engaged with the interactive television service.

32. The apparatus of claim 29, wherein the other users are unrelated individual persons.

33. The apparatus of claim 29, wherein the other users are members of a group and the current user is identifiable as a potential member of that group.

34. The apparatus of claim 29, further comprising:

means for periodically updating the first collection of data to reflect the other users'"'"' ongoing participation in additional activities.

35. The apparatus of claim 34, wherein the means for periodically updating operates in real time, during the current user'"'"'s engagement with the interactive television service.

36. The apparatus of claim 29, further comprising:

means for accessing a second collection of data comprising data associated with;

(i) A plurality of activities that are available via the interactive television service and

(ii) information about each of the plurality of available activities distinguishing the activity from others of the plurality of the available activities,

wherein the means for attributing includes means for selecting, from the plurality of available activities and based on the second collection of data, one or more activities in which the current user is most likely to participate during the engagement with the interactive television service.

37. The apparatus of claim 29, wherein:

the interactive television service is accessed through the Internet,

the activities of the current user and the cumulative activities of the other users include visits to Internet web sites, and

the first collection of data further comprises data associated with;

(i) An identity of each other user,

(ii) types of Internet web sites that each other user has visited,

(iii) content of each type of Internet web site visited by each other user, and

(iv) Amount of time spent at each type of Internet web site by each other user.