SYSTEM AND METHOD FOR PROVIDING TARGETED RATING OF PROFILES IN VIDEO AUDIENCES

• US 20090055860A1
• Filed: 08/19/2008
• Published: 02/26/2009
• Est. Priority Date: 08/20/2007
• Status: Abandoned Application

• Current Assignee: Ads-Vantage, Ltd.
• Original Assignee: Ads-Vantage, Ltd.
• Inventors: Paker, Alex, Litvak-Hinenzon, Anna, Knoller, Raviv, Cohen, Reuven
• Application Number:
  US12/194,236
• Publication Number:
  US 20090055860A1
• Time in Patent Office: Days
• US Class Current: 725/34
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0264 based upon schedule
• CPC Class Codes: G06Q 30/04 Billing or invoicing
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]
• CPC Class Codes: H04N 21/23424 involving splicing one content stream with another content stream, e.g. for inserting or substituting an advertisement
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data
• CPC Class Codes: H04N 21/2665 Gathering content from different sources, e.g. Internet and satellite
• CPC Class Codes: H04N 21/44222 Analytics of user selections, e.g. selection of programs or purchase activity monitoring of user selections in data processing systems G06F11/34; arrangements for monitoring the user's behaviour or opinions in broadcast systems H04H60/33
• CPC Class Codes: H04N 21/6405 Multicasting data broadcast and multicast in packet switching networks H04L12/18
• CPC Class Codes: H04N 21/812 involving advertisement data advertising per se G06Q30/02
• CPC Class Codes: H04N 7/17318 Direct or substantially direct transmission and handling of requests

Abstract

A system and method for providing targeted rating of profiles in video audiences is provided. The method includes the steps of deriving a first input set, wherein the first input set contains data showing which viewer profiles are associated with which set top boxes within the network, wherein the data may also include an association between a single viewer profile and a single set top box within the network; deriving a second input set containing data of at least one set top box signature, wherein the data of the at least one set top box signature further comprises a processed zapping log containing information summarizing viewing habits of at least one set top box within the network; and processing the first input set and the second input set assuming that the second input set can be derived by operations, wherein the operations involve data associating the viewer profiles to set top boxes within the network and to the targeted rating of profiles.

Claims

1. A method of providing targeted rating of profiles in video audiences of a network, comprising the steps of:

obtaining a first input set, wherein the first input set contains data showing which of one or more viewer profiles are associated with which one or more set top boxes within the network;

obtaining a second input set containing data of at least one set top box signature, wherein the data of the at least one set top box signature further comprises a processed zapping log containing information summarizing viewing habits of at least one set top box within the network; and

processing the first input set and the second input set assuming that the second input set can be derived by operations, wherein the operations involve data associating the viewer profiles to set top boxes within the network and to the targeted rating of profiles.

2. The method of claim 1, wherein the set top box signatures are selected from the group consisting of viewing signatures, time signatures, high-resolution time signatures, and zapping frequency signatures.

3. The method of claim 1, wherein the operations are mathematical operations.

4. The method of claim 1, wherein the first input set is received from an external source.

5. The method of claim 1, wherein the first input set is derived by performing a learning step and an identification step, the learning step comprising using set top box signatures with a list of set top boxes and viewer profiles to provide knowledge of how to associate at least one viewer profile to a set top box of the list of set top boxes within the network, and the identification step comprising recognizing a list of viewer profiles as being associated with a set top box, of the list of set top boxes, based on results of the learning step.

6. The method of claim 5, wherein the learning step further comprises the steps of:

receiving a zapping log and a broadcast schedule, wherein the zapping log includes records of set top box zapping signatures for at least a portion of the set top boxes of the network;

deriving set top box signatures from the zapping log and broadcast schedule;

clustering viewer profiles into groups of viewer profiles using the set top box signatures; and

associating at least one set top box within the network with at least one viewer profile.

7. The method of claim 6, wherein an optimization algorithm is used to perform the step of clustering.

8. The method of claim 5, wherein the learning step further comprises the steps of:

receiving a data sample, wherein the data sample provides an association of viewer profiles to a sample of the set top boxes within the network, wherein a sample of the set top boxes includes one or more of the set top boxes within the network;

receiving a zapping log and a broadcast schedule, wherein the zapping log includes records of set top box zapping signatures for at least a portion of the set top boxes of the network;

deriving set top box signatures from the zapping log and broadcast schedule;

using the set top box signatures with the sample of the set top boxes to derive an association rule of viewer profiles to set top boxes within the network; and

applying the association rule to the set top box signatures to determine a subset of viewer profiles of the viewer profiles associated with a specific set top box of the set top boxes within the network.

9. The method of claim 1, wherein the operations involving data associating the viewer profiles to set top boxes and targeted rating comprises providing a relationship between a set A, a set B, and a set C, where the set C is derived by associating set A to set B, where A represents a set of parameters representing the association of at least one viewer profile to at least one set top box, B represents an aggregation of targeted rating values of each of the viewer profiles per each content watched by at least a portion of the set top boxes of the network for which the zapping log contains records of set top box zapping signatures, and C is an aggregation of the set top box signatures.

10. The method of claim 1, wherein the operations involving data associating the viewer profiles to set top boxes and targeted rating comprises providing a relationship between a matrix A, a matrix B, and a matrix C, where matrix A multiplied by matrix B approximates matrix C, where A represents a set of parameters representing the association of at least one viewer profile to set top boxes, B represents an aggregation of targeted rating values of each of the viewer profiles per each content watched by at least a portion of the set top boxes of the network for which the zapping log contains records of set top box zapping signatures, and C is an aggregation of the set top box signatures.

11. The method of claim 1, wherein the set top box signatures comprise at least one signature for each set top box in the network.

12. The method of claim 1, wherein if the network covers more than one region and information on the regions in which different set top boxes in the network reside is available, the method further comprises the step of calculating a regional targeted rating.

13. The method of claim 1, wherein the data of the at least one set top box signature further comprises a processed broadcast schedule containing content that the set top box is capable of receiving

14. A system for providing targeted rating of profiles in video audiences of a network, wherein the system comprises a head end having a computer and means for communicating therein, wherein the computer has a management application stored therein, and wherein the management application further comprises:

logic configured to obtain a first input set, wherein the first input set contains data showing which viewer profiles are associated with which set top boxes within the network, wherein the data may also include an association between a single viewer profile and a single set top box within the network;

logic configured to obtain a second input set containing data of at least one set top box signature, wherein the data of the at least one set top box signature further comprises a processed zapping log containing information summarizing viewing habits of at least one set top box within the network; and

logic configured to process the first input set and the second input set assuming that the second input set can be derived by operations, wherein the operations involve data associating the viewer profiles to set top boxes within the network and to the targeted rating of the profiles.

15. The system of claim 14, wherein the set top box signatures are selected from the group consisting of viewing signatures, time signatures, high-resolution time signatures, and zapping frequency signatures.

16. The system of claim 14, wherein the operations are mathematical operations.

17. The system of claim 14, wherein the first input set is received from an external source.

18. The system of claim 14, wherein the first input set is derived by performing a learning step and an identification step, the learning step comprising using set top box signatures with a list of set top boxes and viewer profiles to provide knowledge of how to associate at least one viewer profile to a set top box of the list of set top boxes within the network, and the identification step comprising recognizing a list of viewer profiles as being associated with a set top box, of the list of set top boxes, based on results of the learning step.

19. The system of claim 18, wherein the learning step further comprises the steps of:

receiving a zapping log and a broadcast schedule, wherein the zapping log includes records of set top box zapping signatures for at least a portion of the set top boxes of the network;

deriving set top box signatures from the zapping log and broadcast schedule;

clustering viewer profiles into groups of viewer profiles using the set top box signatures; and

associating at least one set top box within the network with at least one viewer profile.

20. The system of claim 19, wherein an optimization algorithm is used to perform the step of clustering.

21. The system of claim 18, wherein the learning step further comprises the steps of:

receiving a data sample, wherein the data sample provides an association of viewer profiles to a sample of the set top boxes within the network, wherein a sample of the set top boxes includes one or more of the set top boxes within the network;

receiving a zapping log and a broadcast schedule, wherein the zapping log includes records of set top box zapping signatures for at least a portion of the set top boxes of the network;

deriving set top box signatures from the zapping log and broadcast schedule;

using the set top box signatures with the sample of the set top boxes to derive an association rule of viewer profiles to set top boxes within the network; and

applying the association rule to the set top box signatures to determine a subset of viewer profiles of the viewer profiles associated with a specific set top box of the set top boxes within the network.

22. The system of claim 14, wherein the operations involving data associating the viewer profiles to set top boxes and targeted rating comprises providing a relationship between a set A, a set B, and a set C, where the set C is derived by associating set A to set B, where A represents a set of parameters representing the association of at least one viewer profile to set top boxes, B represents an aggregation of targeted rating values of each of the viewer profiles per each content watched by at least a portion of the set top boxes of the network for which the zapping log contains records of set top box zapping signatures, and C is an aggregation of the set top box signatures.

23. The system of claim 14, wherein the set top box signatures comprise at least one signature for each set top box in the network.

24. The system of claim 14, wherein if the network covers more than one region and information on the regions in which different set top boxes in the network reside is available, the method further comprises the step of calculating a regional targeted rating.

25. The system of claim 14, wherein the data of the at least one set top box signature further comprises a processed broadcast schedule containing content that the set top box is capable of receiving.