Behavioral keyword identification based on thematic channel viewing

• US 9,639,856 B2
• Filed: 10/23/2015
• Issued: 05/02/2017
• Est. Priority Date: 08/08/2012
• Status: Active Grant

• Current Assignee: Verizon Patent and Licensing Incorporated (Verizon Communications Inc.)
• Original Assignee: Verizon Patent and Licensing Incorporated (Verizon Communications Inc.)
• Inventors: Sankaran, Anand N., Singh, Amitkumar, Madichetti, Nishanth, Parambath, Jubish C., Guntupalli, Anil K., Caputo, Lisa A., Yenda, Govinda R.
• Primary Examiner(s): Lewis, Jonathan V
• Application Number:
  US14/921,304
• Publication Number:
  US 20160055529A1
• Time in Patent Office: 557 Days
• Field of Search: None
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: H04N 21/23109 by placing content in organized collections, e.g. EPG data repository details of retrieval of video data and associated meta data in video databases G06F16/739
• CPC Class Codes: H04N 21/251 Learning process for intelligent management, e.g. learning user preferences for recommending movies details of learning user preferences for the retrieval of video data in a video database G06F16/739; computer systems using learning methods G06N3/08
• CPC Class Codes: H04N 21/25891 being end-user preferences retrieval of video data in a video database based on user preferences G06F16/739; arrangements for recognizing users' preferences H04H60/46; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/44224 Monitoring of user activity on external systems, e.g. Internet browsing
• CPC Class Codes: H04N 21/4532 involving end-user characteristics, e.g. viewer profile, preferences monitoring of user activities for profile generation for accessing a video database G06F16/739; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/4667 Processing of monitored end-user data, e.g. trend analysis based on the log file of viewer selections
• CPC Class Codes: H04N 21/4668 for recommending content, e.g. movies
• CPC Class Codes: H04N 21/47 End-user applications
• CPC Class Codes: H04N 21/47214 for content reservation or setting reminders; for requesting event notification, e.g. of sport results or stock market stock exchange data over packet-switching network H04L12/1804; push services over packet-switching network H04L12/1859; notification of incoming messages in packet switching networks H04L51/224
• CPC Class Codes: H04N 21/482 End-user interface for program selection broadcast systems using EPGs H04H60/72
• CPC Class Codes: H04N 21/4828 for searching program descriptors retrieval of video data G06F16/739
• CPC Class Codes: H04N 21/6582 Data stored in the client, e.g. viewing habits, hardware capabilities, credit card number arrangements where receivers interact with the broadcast H04H20/38
• CPC Class Codes: H04N 21/812 involving advertisement data advertising per se G06Q30/02
• CPC Class Codes: H04N 21/8405 represented by keywords
• CPC Class Codes: H04N 7/17318 Direct or substantially direct transmission and handling of requests

Abstract

A method, performed by a computer device, may include obtaining a viewing history, associated with a customer, from a set-top box associated with the customer, wherein the viewing history relates a particular television channel to a duration time associated with the particular television channel. The method may further include determining a keyword, associated with the customer, based on the obtained viewing history; calculating a keyword score for the keyword based on the obtained viewing history; selecting an advertisement, associated with the keyword, based on the calculated keyword score; and providing the selected advertisement to the set-top box associated with the customer, based on selecting the advertisement.

Claims

1. A method performed by a computer device, the method comprising:

obtaining, by the computer device, a viewing history, associated with a customer, front a mobile device associated with the customer, wherein the viewing history relates a particular content channel to a duration time associated with the particular content channel;

determining, by the computer device, a keyword, associated with the customer, based on the obtained viewing history;

determining, by the computer device, all content channels, in the obtained viewing history, that are associated with the keyword;

determining, by the computer device, a total viewing duration for the keyword based on a sum of the duration times of all the content channels associated with the keyword;

determining, by the computer device, a duration score for the keyword based on the determined total viewing duration for the keyword;

calculating, by the computer device, a keyword score based on the determined duration score;

selecting, by the computer device, an advertisement, associated with the keyword, based on the calculated keyword score; and

providing, by the computer device, the selected advertisement to the mobile device associated with the customer.

2. The method of claim 1, further comprising:

selecting the particular content channel;

identifying one or more categories associated with the selected particular content channel;

assigning a combination identifier to the selected particular content channel based on the identified one or more categories; and

associating one or more keywords with the assigned combination identifier.

3. The method of claim 2, wherein identifying the one or more categories associated with the selected particular content channel includes;

identifying a genre associated with the particular content channel;

identifying a subgenre associated with the particular content channel; and

identifying a language associated with the particular content channel.

4. The method of claim 1, wherein determining the keyword, associated with the customer, based on the obtained viewing history includes:

determining a combination identifier for a particular content channel included in the viewing history, wherein the combination identifier is associated with one or more categories associated with the particular content channel; and

selecting the keyword from a set of one or more keywords associated with the combination identifier.

5. The method of claim 1 wherein a content channel is a content stream.

6. The method of claim 1, wherein calculating the keyword score for the keyword based on the obtained viewing history further includes:

determining a total viewing duration time for the customer based on the obtained viewing history;

determining a percentage score for the keyword based on a ratio of the total viewing duration for the keyword and the total viewing duration time for the customer; and

determining the keyword score based on the determined percentage score.

7. The method of claim 6, wherein calculating the keyword score for the keyword based on the obtained viewing history further includes:

identifying other customers associated with the keyword;

determining a number of the identified other customers associated with the keyword;

determining a total viewing duration for the keyword for each of the identified other customers;

determining a ranking number for the customer with respect to the identified other customers based on the total viewing duration for the keyword for the customer and based on the determined total viewing duration for the keyword for each of the identified other customers;

determining a ranking score for the keyword based on a ratio of the ranking number for the customer and the number of the identified other customers associated with the keyword; and

determining the keyword score based on the determined ranking score.

8. The method of claim 7, further comprising;

determining the keyword score as a weighted average of the determined duration score, the determined percentage score, and the determined ranking score.

9. The method of claim 8, further comprising:

increasing a weight associated with the determined duration score when the total viewing duration time for the customer is higher than a particular thresh old number.

10. The method of claim 8, further comprising;

increasing a weight associated with the determined percentage score when the total viewing duration time for the customer is lower than a particular threshold number.

11. The method of claim 8, further comprising:

increasing a weight, associated with the determined ranking score when a number of content channels associated with the keyword is less than a particular threshold number.

12. A system comprising:

at least one server device configured to;

obtain a viewing history, associated with a customer, from a mobile device associated with the customer, wherein the viewing history relates a particular content channel to a duration time associated with the particular content channel;

determine a keyword, associated with the customer, based on the obtained viewing history;

determine all content channels, in the obtained viewing history, that are associated with the keyword;

determine a total viewing duration for the keyword based on a sum of the duration times of all the content channels associated with the keyword;

determine a duration score for the keyword based on the determined total viewing duration for the keyword;

calculate a keyword score based on the determined duration score;

select an advertisement, associated with the keyword, based on the calculated keyword score; and

provide the selected advertisement to the mobile device associated with the customer, based on selecting the advertisement.

13. The system of claim 12, wherein the at least one server device is further configured to:

select the particular content channel;

identify one or more categories associated with the selected particular content channel;

assign a combination identifier to the selected particular content channel based on the identified one or more categories; and

associate one or more keywords with the assigned combination identifier.

14. The system of claim 12, wherein the at least one server device is further configured to:

determine a combination identifier for a particular content channel included in the viewing history, wherein the combination identifier is associated with one or more categories associated with the particular content channel; and

select the keyword from a set of one or more keywords associated with the combination identifier.

15. The system of claim 12 wherein a content channel is a content stream.

16. The system of claim 12, wherein the at least one server device is further configured to;

determine a total viewing duration time for the customer based on the obtained viewing history;

determine a percentage score for the keyword based on a ratio of the total viewing duration for the keyword and the total viewing duration time for the customer; and

determine the keyword score based on the determined percentage score.

17. The system of claim 16, wherein the at least one server device is further configured to:

identify other customers associated with the keyword;

determine a number of the identified other customers associated with the keyword;

determine a total viewing duration for the keyword for each of the identified other customers;

determine a ranking number for the customer with respect to the identified other customers based on the total viewing duration for the keyword for the customer and based on the determined total viewing duration for the keyword for each of the identified other customers;

determine a ranking score for the keyword based on a ratio of the ranking number for the customer and the number of the identified other customers associated with the keyword; and

determine the keyword score based on the determined ranking score.

18. The system of claim 17, wherein the at least one server device is further configured to:

determine the keyword score as a weighted average of the determined duration score, the determined percentage score, and the determined ranking score.

19. A non-transitory computer-readable medium storing instructions executable by one or more processors, the non-transitory computer-readable medium comprising:

one or more instructions to obtain a viewing history, associated with a customer, from a mobile device associated with the customer, wherein the viewing history relates a particular content channel to a duration time associated with the particular content channel;

one or more instructions to determine a keyword, associated with the customer, based on the obtained viewing history;

one or more instructions to determine all content channels, in the obtained viewing history, that are associated with the keyword;

one or more instructions to determine a total viewing duration for the keyword based on a sum of the duration times of all the content channels associated with the keyword;

one or more instructions to determine a duration score for the keyword based on the determined total viewing duration for the keyword;

one or more instructions to calculate a keyword score based on the determined duration score;

one or more instructions to select an advertisement, associated with the keyword, based on the calculated keyword score; and

one or more instructions to provide the selected advertisement to the mobile device associated with the customer, based on selecting the advertisement.

20. The non-transitory computer-readable medium of claim 19, further comprising:

one or more instructions to determine a total viewing duration time for the customer based on the obtained viewing history;

one or more instructions to determine a percentage score for the keyword based on a ratio of the total viewing duration for the keyword and the total viewing duration time for the customer;

one or more instructions to identify other customers associated with the keyword;

one or more instructions to determine a number of the identified other customers associated with the keyword;

one or more instructions to determine a total viewing duration for the keyword for each of the identified other customers;

one or more instructions to determine a ranking number for the customer with respect to the identified other customers based, on the total viewing duration for the keyword for the customer and based on the determined total viewing duration for the keyword for each of the identified other customers;

one or more instructions to determine a ranking score for the keyword based on a ratio of the ranking number for the customer and the number of the identified other customers associated with the keyword; and

one or more instructions to determine the keyword score as a weighted average of the determined duration score, the determined percentage score, and the determined ranking score.