DISTRIBUTED CONTENT ITEM RECOMMENDATION SYSTEM AND METHOD OF OPERATION THEREFOR

• US 20080243997A1
• Filed: 01/22/2008
• Published: 10/02/2008
• Est. Priority Date: 03/29/2007
• Status: Abandoned Application

• Current Assignee: Motorola Mobility LLC (Lenovo Group Ltd.)
• Original Assignee: Motorola, Inc. (Motorola Solutions, Inc.)
• Inventors: Park, Joon Young, Picault, Jerome, Mercer, Kevin C., Bouzid, Makram, Lhuillier, Nicolas, Bonnefoy, David
• Application Number:
  US12/017,462
• Publication Number:
  US 20080243997A1
• Time in Patent Office: Days
• US Class Current: 709/203
• CPC Class Codes: G06F 2209/5017 Task decomposition
• CPC Class Codes: G06F 2209/509 Offload
• CPC Class Codes: G06F 9/5027 the resource being a machine, e.g. CPUs, Servers, Terminals
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A distributed content item recommendation system comprises a central recommendation server (101) and a plurality of remote recommendation devices (103) coupled to the central recommendation server (101) via a communication network (105). The central recommendation server (101) stores content item set correlation data for sets of content items. The correlation data is used for item based collaborative filtering in recommendation processors (303) of the recommendation devices (103). A computation task processor (207) maintains a task list of content item correlation computation tasks which can be independently executed to generate content item set correlation data. A task assignment processor (209) can assign the computation tasks to remote recommendation devices (103) which comprise a processing unit (307) that calculates the associated correlation data and returns it to the recommendation server (101). The distributed recommendation system thus uses distributed computation of centrally stored correlation data thereby substantially reducing the cost and complexity of the recommendation server and/or improves the recommendations.

Claims

1. A distributed content item recommendation system comprising a central recommendation server and a plurality of remote recommendation devices coupled to the central recommendation server via a communication network;

wherein;

the central recommendation server comprises;

a correlation data store for storing content item set correlation data for sets of content items,

means for providing content item set correlation data to the remote recommendation devices,

means for maintaining a task list of content item correlation computation tasks, each content item correlation computation task determining content item set correlation data for at least one set of content items and each content item correlation computation task being computable independently of other content item correlation computation tasks,

assigning means for assigning content item correlation computation tasks from the task list to remote recommendation devices,

means for receiving first content item set correlation data for a first set of content items from a remote recommendation device assigned a content item correlation computation tasks for the first set, and

means for including the first content item set correlation data in the correlation data store; and

the remote recommendation devices comprise;

means for receiving content item set correlation data from the central recommendation server;

recommendation means for generating a content item recommendation in response to the content item set correlation data;

processing means for executing an assigned content item correlation computation task to generate associated content item set correlation data; and

means for transmitting the associated content item set correlation data to the central recommendation server.

2. The distributed content item recommendation system of claim 1 wherein the content item set correlation data depends on content item ratings and the central recommendation server is arranged to receive content item ratings from the remote recommendation devices.

3. The distributed content item recommendation system of claim 1 wherein the central recommendation server comprises means for generating a content item correlation computation task for the task list in response to the content item ratings.

4. The distributed content item recommendation system of claim 1 wherein at least a first of the remote recommendation devices comprises means for transmitting a request for requested content item set correlation data to the central recommendation server;

and the central recommendation server comprises means for transmitting the requested content item set correlation data to the first remote recommendation device if the requested content item set correlation data meets a validity criterion; and

the recommendation means of the first remote recommendation device is arranged to generate a recommendation in response to the requested content item set correlation data.

5. The distributed content item recommendation system of claim 4 wherein the validity criterion comprises a comparison of a request time with an expiry time of the requested content item set correlation data.

6. The distributed content item recommendation system of claim 5 wherein the remote recommendation devices comprise means for time stamping associated content item set correlation data transmitted to the central recommendation server.

7. The distributed content item recommendation system of claim 4 wherein the central recommendation server comprises means for generating a first content item correlation computation task for the task list if the requested content item set correlation data does not meet the validity criterion.

8. The distributed content item recommendation system of claim 7 wherein the assigning means is arranged to assign the first content item correlation computation task to the first remote recommendation device.

9. The distributed content item recommendation system of claim 4 wherein the central recommendation server comprises means for transmitting a wait indication to the first remote recommendation device in response to a determination that a content item correlation computation task for the requested content item set correlation data is currently assigned.

10. The distributed content item recommendation system of claim 1 wherein the content item correlation computation tasks are at least partly represented by a set of content item ratings.

11. The distributed content item recommendation system of claim 1 wherein the content item correlation computation tasks are at least partly represented by an indication of a correlation algorithm to be used for determining the content item set correlation data.

12. The distributed content item recommendation system of claim 1 wherein the remote recommendation devices comprise means for requesting an assignment of a content item correlation computation task in response to a determination of an available computational resource of the remote recommendation device.

13. The distributed content item recommendation system of claim 1 wherein the central recommendation server comprises means for executing an assigned content item correlation computation task to generate associated content item set correlation data;

and means for requesting an assignment of a content item correlation computation task in response to a determination of an available computational resource of the central recommendation server.

14. The distributed content item recommendation system of claim 1 wherein the central recommendation server comprises means for transmitting unrequested content item set correlation data to remote recommendation devices in response to receiving the unrequested content item set correlation data from an assigned content item correlation computation task.

15. The distributed content item recommendation system of claim 1 further comprising means for performing a distributed execution of a content item correlation computation task between the processing means of a plurality of remote recommendation devices.

16. A central recommendation server for a distributed content item recommendation system further including a plurality of remote recommendation devices coupled to the central recommendation server via a communication network;

the central recommendation server comprising;

a correlation data store for storing content item set correlation data for sets of content items;

means for providing content item set correlation data to the remote recommendation devices;

means for maintaining a task list of content item correlation computation tasks, each content item correlation computation task determining content item set correlation data for at least one set of content items and each content item correlation computation task being computable independently of other content item correlation computation tasks;

means for assigning content item correlation computation tasks from the task list to remote recommendation devices;

means for receiving first content item set correlation data for a first set of content items from a remote recommendation device assigned a content item correlation computation task for the first set; and

means for including the first content item set correlation data in the correlation data store.

17. A method of operation for a distributed content item recommendation system comprising a central recommendation server and a plurality of remote recommendation devices coupled to the central recommendation server via a communication network;

the method comprising;

the central recommendation server performing the steps of;

storing content item set correlation data for sets of content items in a correlation data store,

providing content item set correlation data to the remote recommendation devices,

maintaining a task list of content item correlation computation tasks, each content item correlation computation task determining content item set correlation data for at least one set of content items and each content item correlation computation task being computable independently of other content item correlation computation tasks,

assigning content item correlation computation tasks from the task list to remote recommendation devices,

receiving first content item set correlation data for a first set of content items from a remote recommendation device assigned a content item correlation computation task for the first set, and

including the first content item set correlation data in the correlation data store; and

and the remote recommendation device performs the steps of;

receiving content item set correlation data from the central recommendation server,

generating a content item recommendation in response to the content item set correlation data,

executing an assigned content item correlation computation task to generate associated content item set correlation data, and

transmitting the associated content item set correlation data to the central recommendation server.