PROVIDING DIGITAL ASSETS AND A NETWORK THEREFOR

• US 20100070571A1
• Filed: 09/14/2009
• Published: 03/18/2010
• Est. Priority Date: 09/15/2008
• Status: Abandoned Application

• Current Assignee: Alcatel-Lucent SA (Nokia Corporation)
• Original Assignee: Alcatel-Lucent SA (Nokia Corporation)
• Inventors: Robinson, Dave Cecil, Kisel, Andrey
• Application Number:
  US12/559,011
• Publication Number:
  US 20100070571A1
• Time in Patent Office: Days
• US Class Current: 709/203
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/40 of multimedia data, e.g. slideshows comprising image and additional audio data retrieval of still image data G06F16/50; retrieval of audio data G06F16/60; retrieval of video data G06F16/70
• CPC Class Codes: G06F 16/48 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9536 Search customisation based on social or collaborative filtering
• CPC Class Codes: H04L 65/612 for unicast
• CPC Class Codes: H04L 67/289 Intermediate processing functionally located close to the data consumer application, e.g. in same machine, in same home or in same sub-network
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/56 Provisioning of proxy services store-and-forward switching systems in data switching networks H04L12/54
• CPC Class Codes: H04L 67/5681 Pre-fetching or pre-delivering data based on network characteristics
• CPC Class Codes: H04L 67/5682 Policies or rules for updating, deleting or replacing the stored data
• CPC Class Codes: H04N 21/222 Secondary servers, e.g. proxy server, cable television Head-end provisioning of proxy services in data packet switching networks H04L67/56
• CPC Class Codes: H04N 21/23106 involving caching operations prefetching while addressing of a memory level in which the access to the desired data or data block requires associative addressing means within memory systems or architectures G06F12/0862; caching at an intermediate stage in a data network H04L67/568
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data
• CPC Class Codes: H04N 21/4668 for recommending content, e.g. movies
• CPC Class Codes: H04N 21/47202 for requesting content on demand, e.g. video on demand
• CPC Class Codes: H04N 7/17336 Handling of requests in head-ends

Abstract

A method is provided of providing digital assets in a network comprising a central controller connected to a plurality of servers. Each asset comprises at least one of video data and audio data. Each server serves a group of user terminals by storing a respective selected set of the assets and providing an asset from the selected set to a user terminal on request. The method comprises, for at least one of the servers, selecting which assets to store by the steps of: (a) for each of the group of user terminals served by the server receiving a recommendation as to a set of assets predicted as most likely to be desired by the individual user terminal, said recommendations being adapted to the individual users of said individual user terminals; (b) determining from the recommendations, a list of the most likely to be requested assets for the group of user terminals; and (c) updating the assets stored in the server so that the listed most likely to be requested assets are stored in the server.

Claims

1. A method of providing digital assets in a network comprising a central controller connected to a plurality of servers, each asset comprising at least one of video data and audio data, each server serving a group of user terminals by storing a respective selected set of the assets and providing an asset from the selected set to a user terminal on request, the method comprising:

for at least one of the servers selecting which assets to store by the steps of;

(a) for each of the group of user terminals served by the server receiving a recommendation as to a set of assets predicted as most likely to be desired by the individual user terminal, said recommendations being adapted to the individual users of said individual user terminals;

(b) determining from the recommendations a list of the most likely to be requested assets for the group of user terminals; and

(c) updating the assets stored in the server so that the listed most likely to be requested assets are stored in the server.

2. A method of providing digital assets according to claim 1, in which generation of the recommendations received in step (a) includes favouring assets selected by other user terminals having related user profiles.

3. A method of providing digital assets according to claim 1, in which generation of the recommendations received in step (a) includes favouring assets of an asset type preferred by the user or related to said asset type.

4. A method of providing digital assets according to claim 1, in which each server are connected to user terminals via a respective set of Digital Subscriber Line Access Multipliers (DSLAMs), and sets of user terminals connected to each DSLAM are considered in turn to determine the list of most likely to be requested assets for the group of user terminals.

5. A method of providing digital assets according to claim 1, in which the step (b) of determining from the recommendations a list of the most likely to be requested assets for the group of user terminals includes incrementing a count associated with the asset on a list of assets upon the asset being recommended for a user terminal, then reordering the list to be in a decreasing order of counts so as to provide the list of the most likely to be requested assets.

6. A method of providing digital assets according to claim 5, in which the step of (c) updating the assets stored in the server so that the listed most likely to be requested assets are stored in the server includes working down through said list of the most likely to be requested assets by checking whether the asset is already stored, and if not stored, checking whether that asset has a count higher than the asset with the lowest count that was stored previously.

7. A method of providing digital assets according to claim 5, in which counts are weighted such that a recommendation of an asset to a user terminal that is frequently used carries more weight than a recommendation of an asset to a less frequent user.

8. A method of providing digital assets according to claim 1, in which recommendations for an individual user terminal are updated dependent on information from said user terminal as to preferences of other users, or type of users, known to said individual user.

9. A method of providing digital assets according to claim 1, in which recommendations are updated dependent on information from an expert.

10. A method of providing digital assets according to claim 1, in which the method is repeated upon at least some recommendations for individual users being updated.

11. A method of providing digital assets according to claim 1, in which the user terminal is sent a list of suggestions of assets to request, the list of suggestions being limited to assets stored in the server.

12. A network for providing digital assets comprising a central controller connected to a plurality of servers, each asset comprising at least one of video data and audio data, each server comprising a memory and being configured to serve a group of user terminals by storing a respective selected set of the assets in the memory and providing an asset from the selected set to a user terminal on request, the network further comprising:

a content controller configured to, for at least one of the servers, select which assets to store;

the content controller being configured to;

(a) for each of the group of user terminals served by the server, receive a recommendation from a recommendation engine as to a set of assets predicted as most likely to be desired by the individual user terminal, said recommendations having been adapted to the individual users of said individual user terminals;

(b) determine from the recommendations, a list of the most likely to be requested assets for the group of user terminals;

(c) control updating of the assets stored in the server so that the listed most likely to be requested assets are stored in the server.