Recommending Groups of Items Based on Item Ranks

• US 20120096013A1
• Filed: 10/14/2010
• Published: 04/19/2012
• Est. Priority Date: 10/14/2010
• Status: Active Grant

• Current Assignee: Netflix, Inc.
• Original Assignee: Netflix, Inc.
• Inventors: Sanders, Jonathan Michael, Hunt, Neil D., Ciancutti, John, Yellin, Todd Scot
• Granted Patent: US 8,903,834 B2
• Time in Patent Office: Days
• US Class Current: 707/749
• CPC Class Codes: G06F 16/435 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/907 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually

Abstract

One embodiment of the invention sets forth a mechanism for recommending digital items to a user. Each digital item in a set of digital items is scored based on user preferences and other metrics. The digital items are ordered based on scores. The digital items are then evaluated in order of respective rank to determine a subset of digital items that re recommended to the user. The evaluation process is based on different evaluation criteria as well as the presentation style of the recommended digital items.

Claims

1. A computer-implemented method for recommending digital items to a user, the method comprising:

for each digital item in a set of digital items, computing a desirability score based on one or more scoring metrics; and

evaluating, in order, one or more digital items in the set of digital items to determine a subset of digital items to recommend to the user.

2. The method of claim 1, further comprising the step of, for each digital item in the set of digital items, determining a rank relative to the other digital items in the set of digital items based on the desirability score associated with the digital item, wherein the set of digital items are ordered based on the rank associated with each digital item.

3. The method of claim 1, wherein the step of evaluating one or more digital items comprises applying a first evaluation function to each of the one or more digital items to determine whether the digital item should be recommended to the user.

4. The method of claim 3, wherein the first evaluation function specifies that only a digital item having a high rating should be recommended to the user.

5. The method of claim 1, wherein the step of evaluating the one or more digital items comprises identifying one or more metadata tags associated with a first digital item of the one or more digital items.

6. The method of claim 5, wherein the step of evaluating the one or more digital items further comprises determining a set of group definitions corresponding to the one or more digital items, wherein each group definition is defined by a different set of metadata tags, each group definition includes at least one digital item of the one or more digital items, and each metadata tag defining a group definition is included in the one or more metadata tags associated with the at least one digital item included in the group definition.

7. The method of claim 6, further comprising the steps of:

computing a score for each group definition in the set of group definitions based on scoring mechanism; and

selecting a first group definition of the set of group definitions based on the score computed for each group definition, wherein each digital item included in the first group definition is recommended to the user.

8. The method of claim 7, further comprising the steps of:

removing each digital item included in the first group definition from the remaining group definitions; and

re-computing a score for each group definition in the remaining group definitions based on the scoring mechanism.

9. The method of claim 7, wherein the scoring mechanism is based on the number of digital items associated with a group definition.

10. The method of claim 7, wherein the scoring mechanism is based on the number of metadata tags associated with a group definition.

11. A computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to recommend digital items to a user, by performing the steps of:

for each digital item in a set of digital items, computing a desirability score based on one or more scoring metrics;

ordering the set of digital items based on the desirability score associated with each digital item in the set of digital items; and

evaluating, in order, one or more digital items in the set of digital items to determine a subset of digital items to recommend to the user.

12. The computer-readable storage medium of claim 11, further comprising the step of, for each digital item in the set of digital items, determining a rank relative to the other digital items in the set of digital items based on the desirability score associated with the digital item, wherein the set of digital items are ordered based on the rank associated with each digital item.

13. The computer-readable storage medium of claim 11, wherein the step of evaluating one or more digital items comprises applying a first evaluation function to each of the one or more digital items to determine whether the digital item should be recommended to the user.

14. The computer-readable storage medium of claim 13, wherein the first evaluation function specifies that only a digital item having a high rating should be recommended to the user.

15. The computer-readable storage medium of claim 11, wherein the step of evaluating the one or more digital items comprises identifying one or more metadata tags associated with a first digital item of the one or more digital items.

16. The computer-readable storage medium of claim 15, wherein the step of evaluating the one or more digital items further comprises determining a set of group definitions corresponding to the one or more digital items, wherein each group definition is defined by a different set of metadata tags, each group definition includes at least one digital item of the one or more digital items, and each metadata tag defining a group definition is included in the one or more metadata tags associated with the at least one digital item included in the group definition.

17. The computer-readable storage medium of claim 16, further comprising the steps of:

computing a score for each group definition in the set of group definitions based on scoring mechanism; and

selecting a first group definition of the set of group definitions based on the score computed for each group definition, wherein each digital item included in the first group definition is recommended to the user.

18. The computer-readable storage medium of claim 17, further comprising the steps of:

removing each digital item included in the first group definition from the remaining group definitions; and

re-computing a score for each group definition in the remaining group definitions based on the scoring mechanism.

19. The computer-readable storage medium of claim 17, wherein the scoring mechanism is based on the number of digital items associated with a group definition.

20. The computer-readable storage medium of claim 17, wherein the scoring mechanism is based on the number of metadata tags associated with a group definition.

21. A system, comprising:

a memory; and

a processor configured to;

for each digital item in a set of digital items, compute a desirability score based on one or more scoring metrics,

order the set of digital items based on the desirability score associated with each digital item in the set of digital items, and

evaluate, in order, one or more digital items in the set of digital items to determine a subset of digital items to recommend to the user.