Recommendation network

• US 20070064626A1
• Filed: 08/21/2006
• Published: 03/22/2007
• Est. Priority Date: 08/19/2005
• Status: Active Grant

• Current Assignee: SitNet LLC
• Original Assignee: Evree, LLC
• Inventors: Evans, Matthew
• Granted Patent: US 7,761,399 B2
• Time in Patent Office: Days
• US Class Current: 370/254
• CPC Class Codes: G06F 16/958 Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

A recommendation network is described. The recommendation network may include, but is not limited to, users or entities (“recommendation sources,”) that explicitly or implicitly recommend, rate or refer items and users or entities that receive recommendations or referrals (“recommendation receivers,”). Users who make recommendations can create multiple recommendation sources, using different recommendation sources for different purposes, by assigning different recommendations to different recommendation sources. The recommendation network allows recommendation receiver to assign relative trust ratings to recommendation sources, the relative trust rating representing the recommendation receiver'"'"'s confidence that the recommendation source, compared to other recommendation sources, makes recommendations the recommendation receiver considers valuable. The relative trust ratings can be ordinal or cardinal values that can be used by the network algorithm to filter and rank items for the recommendation receiver. The network may rank items for the recommendation receiver based on the number of recommendation source referencing the item and the relative trust rating the recommendation receiver has assigned to those recommendation sources. By ranking items for each recommendation receiver according to the a ranking algorithm that uses the relative trust ratings the recommendation receiver has assigned to those recommendation source, the network allows the recommendation receiver to receive recommendations for items in the form of a ranked list, the items being ranked by the degree they are recommended by the recommendation receiver'"'"'s trusted recommendation sources. By allowing the recommendation receiver to assign relative trust ratings to different recommendation source, and by ranking and displaying recommendations by the degree to which they are recommended to the recommendation receiver, the network allows users to subscribe to, or receive, recommendations from a limitless number of recommendation sources without being overwhelmed. The network prioritizes the recommendations for an recommendation receiver by the parameters the recommendation receiver establishes, imposing order on a potentially-limitless number of pushed recommendations. According to an embodiment of the invention, a recommendation receiver can be a recommendation source, and can create recommendation sources, for themselves or other recommendation receivers. The recommendation receiver may explicitly or implicitly recommend items as a recommendation source, and can also recommend other recommendation sources, or re-label other recommendation sources, or rate multiple recommendation sources and combine them, to create new recommendation sources. Besides combining multiple recommendation sources to create a new recommendation source, recommendation receivers can create new recommendation sources by restricting the new recommendation source to include only those recommendations, from one or more existing recommendation sources, that share or avoid particular characteristics. The new recommendation sources may in turn be used by the recommendation receiver, or other recommendation receivers. Other recommendation receivers can assign relative trust values to the new recommendation sources. Therefore, by interpreting or reinterpreting received recommendation sources to create new recommendation sources, then by recommending those new recommendation sources, the recommendation receiver provides more information, which helps other recommendation receivers to identify valuable recommendations and information about items.

Claims

1. A system, comprising:

a first device for a first recommendation source to assign a trust rating to a second recommendation source in a recommendation network, the trust rating representing the degree of trust that the first recommendation source has in the second recommendation source to provide a noteworthy first recommendation, the trust rating to be processed by a computer to organize the first recommendation into a ranked list, and the first device to allow the first recommendation source to associate a recommendation channel with a first recommendation bundle.

2. The system of claim 1, where the recommendation channel comprises any one of a first topic channel and a second recommendation bundle.

3. The system of claim 2, where the first device is also for the first recommendation source to make a second recommendation.

4. The system of claim 3, where the first device is also for the first recommendation source to assign to the second recommendation any one of a value rating and a temporality rating.

5. The system of claim 3, where the first device is also for the first recommendation source to assign the second recommendation to any one of the first topic channel and one or more additional topic channels.

6. The system of claim 2, where the first device is also for the first recommendation source to create any one of the first topic channel and the second recommendation bundle.

7. The system of claim 1, where the first device is also for the first recommendation source to filter a recommendation channel.

8. A method, comprising:

receiving a first recommendation from a first recommendation source;

assigning a first trust rating to the first recommendation source, wherein the trust rating represents the degree that a second recommendation source has in the first recommendation source to provide a noteworthy recommendation, the trust rating to be processed by a computer; and

assigning the first recommendation from the first recommendation source to a first recommendation bundle.

9. The method of claim 8, further comprising submitting the first trust rating to a processing unit to be processed by the computer to assign the first recommendation into a ranked list.

10. The method of claim 8, where the first recommendation comprises any one of a first topic channel and a second recommendation bundle.

11. The method of claim 8, further comprising making a second recommendation.

12. The method of claim 11 further comprising assigning any one of a value rating and a temporality rating to the second recommendation.

13. The method of claim 11 further comprising assigning the second recommendation to one or more topic channels.

14. The method of claim 13, further comprising creating any one of the one or more topic channels.

15. The method of claim 8 further comprising creating any one of the first recommendation bundle or a second recommendation bundle.

16. The method of claim 8, where the first recommendation is in a first recommendation channel, and further comprising filtering the first recommendation channel to filter out one or more specific recommendations.

17. A computer-readable medium with contents that can cause a computing system to carry out a method comprising:

assigning a first trust rating to a first recommendation source, wherein the trust rating represents the degree that a second recommendation source has in the first recommendation source to provide a noteworthy recommendation, the trust rating to be processed by a computer; and

assigning the first recommendation from the first recommendation source to a first recommendation bundle.

18. The computer-readable medium of claim 17, further comprising submitting the first trust rating to a processing unit to be processed by the computer to assign the first recommendation into a ranked list.

19. The computer-readable medium of claim 18, further comprising processing the trust rating with a recommendation value rating to produce a score.

20. The computer-readable medium of claim 17, where the first recommendation comprises any one of a first topic channel and a second recommendation bundle.