CONTENT ON DEMAND EDGE CACHE RECOMMENDATIONS

• US 20130144750A1
• Filed: 01/29/2013
• Published: 06/06/2013
• Est. Priority Date: 07/28/2009
• Status: Active Application

• Current Assignee: Comcast Cable Communications LLC (Comcast Corporation)
• Original Assignee: Comcast Cable Communications LLC (Comcast Corporation)
• Inventors: Brown, Tom
• Application Number:
  US13/753,301
• Publication Number:
  US 20130144750A1
• Time in Patent Office: Days
• US Class Current: 705/26.7
• CPC Class Codes: G06F 16/435 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/4387 by the use of playlists
• CPC Class Codes: G06F 16/489 using time information
• CPC Class Codes: G06Q 30/0277 Online advertisement
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

Methods and systems for providing content and content recommendations are described. Content recommendations for users in a service area may be based on content requests from users within the same service area. Content recommendations over a period of time may dynamically change based on many factors, including: the number of requests for particular content within one or more time frames, the storage location of requested content relative to requesting users, and whether a request occurs within a time period of rapid shift in use and types of content requested. A content recommendation including one or more content recommendations may be provided to users.

Claims

1. A method comprising:

capturing, for each of a plurality of content items, information related to a number of times said each content item was requested in a predetermined time period and the geographic area from which it was requested; and

creating a content recommendation for users in a first geographic area, wherein the recommendation identifies one or more content items selected from the plurality of content items, wherein each content item in the recommendation is prioritized according to weighting criteria, wherein one weighting criterion relates to time elapsed from when a request for said each content item was made.

2. The method of claim 1, wherein requests for the content items in the recommendation occur within one of a first time frame and a second time frame having a start time earlier than the first time frame.

3. The method of claim 2, further comprising:

grouping the content items in the content recommendation according to the first time frame and the second time frame; and

sorting content items within each group according to a number of requests from users in the first geographic area each content item has within the corresponding time frame.

4. The method of claim 2, further comprising:

calculating a score for a first content item based on the number of requests from users in the first geographic area for the first content item within the first time frame and the number of requests from users in the first geographic area for the first content item within the second time frame, and one or more weights assigned to counts in the first time frame and to counts in the second time frame; and

placing an identification of the first content item in the content recommendation based on the score.

5. The method of claim 4, wherein the content recommendation comprises a list, and wherein placing the identification of the first content item in the content recommendation list based on the score includes:

placing the identification of the first content item at a beginning of the list when the score is greater than other scores calculated for other content items identified by the content recommendation list.

6. The method of claim 1, further comprising:

transmitting the content recommendation to at least one client device within the first geographic area.

7. The method of claim 1, wherein the content item includes video content.

8. A method comprising:

capturing, for each of a plurality of content items maintained at one or more of a plurality of network locations, a first one or more counts indicating how many requests have been received for the respective content item within a first period of time;

for each content item, determining the network location of the content item and a popularity score based on the first one or more counts and the network location of the content item; and

creating a content recommendation that identifies one or more content items of the plurality of content items, wherein the arrangement of the content recommendation is based on the popularity scores.

9. The method of claim 8, wherein the plurality of network locations include at least one of an edge cache, a gateway server, and a master library, wherein the edge cache is configured to transmit content to client devices within a service area of a content delivery network.

10. The method of claim 9, further comprising:

increasing the score of a content item based on a determination that the content item is stored at the edge cache; and

decreasing the score of a content item based on a determination that the content item is stored at one or more of the gateway server and the master library.

11. The method of claim 8, further comprising:

capturing, for each of the plurality of content items, a second one or more counts indicating how many requests have been received for the respective content item within a second period of time,

wherein determining the popularity score for each content item includes;

determining a first weight corresponding to the first period of time and a second weight corresponding to the second period of time;

determining that a request for a content item of the plurality of content items occurs within a predetermined time period, wherein the predetermined time period indicates a period of rapid change of content requests;

in response to determining that the request occurs within the predetermined time period, adjust the first and second weights; and

determining the popularity scores based on the adjusted first and second weights.

12. The method of claim 11, wherein:

the second period of time comprises the first period of time; and

adjusting the first and second weights includes increasing the first weight and decreasing the second weight.

13. The method of claim 8, further comprising:

for a content item of the plurality of content items, determining whether the content item is stored at an edge cache connected to a service area of a content delivery network; and

if the popularity score of the content item exceeds a predetermined threshold and the content item is not stored at the edge cache, storing the content item at the edge cache.

14. The method of claim 8, wherein the content recommendation comprises a list, the method further comprising:

for a content item of the plurality of content items, determining whether the content item is stored at an edge cache connected to a service area of a content delivery network; and

if the content item is positioned above a predetermined position on the content recommendation list and the content item is not stored at the edge cache, storing the content item at the edge cache.

15. A method comprising:

identifying a service area of a network, the service area including an edge cache configured to transmit content to user devices within the service area;

identifying a number of requests received for each of a plurality of content items occurring within a first time frame and a second time frame;

for each said content item, determining a popularity score based on the number of requests for the content item in the first time frame and the number of requests for the content item in the second time frame; and

generating a content recommendation that identifies one or more content items selected from the plurality of content items having a popularity score greater than a predetermined popularity score threshold.

16. The method of claim 15, further comprising:

determining a first weight corresponding to the first time frame and a second weight corresponding to the second time frame, the second weight different from the first weight,

wherein determining the popularity score for each content item includes calculating the popularity score based on the first and second weights and the number of requests for the content item in the first and second time frames.

17. The method of claim 16, further comprising:

determining that a request for the content recommendation occurs within a predetermined time period, wherein the predetermined time period indicates a period of rapid change of content requests;

in response to determining that the request occurs within the predetermined time period, adjusting the first and second weights; and

determining the popularity score for each content item based on the adjusted first and second weights and the number of requests for the content item in the first and second time frames.

18. The method of claim 17, wherein:

the second time frame includes the first time frame, and

adjusting the first and second weights includes increasing the first weight and decreasing the second weight.

19. The method of claim 17, wherein:

the first time frame is more recent than the second time frame, and

adjusting the first and second weights includes increasing the first weight and decreasing the second weight.

20. The method of claim 15, further comprising:

transmitting the content recommendation to a client device within the service area.