Ranking and ordering items in user-streams

• US 8,874,559 B1
• Filed: 10/01/2012
• Issued: 10/28/2014
• Est. Priority Date: 10/01/2012
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Wyatt, Daniel, Tomkins, Andrew, Karimzadehgan, Maryam
• Primary Examiner(s): Leroux, Etienne
• Assistant Examiner(s): Nguyen, Cindy
• Application Number:
  US13/632,308
• Time in Patent Office: 757 Days
• Field of Search: 707/723, 707/707
• US Class Current: 707/723
• CPC Class Codes: G06F 16/24568 Data stream processing; Continuous queries
• CPC Class Codes: G06F 16/24578 using ranking

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying a set of items that are displayed to a user of a social networking service, the items comprising digital content distributed using the social networking service and being associated with item features, the item features comprising item-dependent features and user-dependent features; receiving feature values that are associated with one of an item-dependent feature and a user-dependent feature; receiving probabilities that are associated with a group and reflecting a likelihood that the user is a type of user associated with the group, the groups including a set of weights; determining an item score based on the feature values and a set of weights to provide item scores, the set of weights being identified based on the probabilities; and determining a subset of items to be displayed to the user based on the item scores.

Claims

1. A system comprising:

a computing device; and

a computer-readable medium coupled to the computing device and having instructions stored thereon which, when executed by the computing device, cause the computing device to perform operations comprising;

identifying a set of items that are displayed to a user of a social networking service, one or more items of the set of items comprising digital content distributed using the social networking service and being associated with a plurality of item features, the plurality of item features comprising item-dependent features and user-dependent features;

for one or more items in the set of items, receiving a plurality of feature values, each of the feature values for each item of the one or more items being associated with one of an item-dependent feature and a user-dependent feature;

receiving a plurality of probabilities, each of the probabilities of the plurality of probabilities being associated with a group of a plurality of groups and reflecting a likelihood that the user is a type of user associated with the group, each group of the plurality of groups including a set of weights, wherein each weight of each group is associated with an item feature of the one or more items;

for one or more items in the set of items, determining an item score for the item based on i) for each group, a weighted feature value associated with each item feature of the item for the group and ii) the probability associated with each group, wherein the weighted feature value for each item feature for each group is based on i) the feature value of the item feature and ii) the weight associated with the item feature for the group; and

determining a subset of items to be displayed to the user based on the item scores for each of the one or more items, the subset of items comprising items of the plurality of items.

2. The system of claim 1, wherein the weighted feature value for each item feature for each group is based on a product of i) the feature value of the item feature and ii) the weight associated with the item feature for the group.

3. The system of claim 1, wherein the probabilities in the plurality of probabilities vary based on activity of the user within the social networking service.

4. The system of claim 1, wherein determining the item score comprises selecting a group based on the plurality of probabilities, the item score being determined based on the set of weights associated with the group.

5. The system of claim 4, wherein selecting a group based on the plurality of probabilities comprises selecting the group having a highest probability.

6. The system of claim 1, wherein the operations further comprise transmitting instructions to display items in the subset of items to the user.

7. The system of claim 6, wherein the operations further comprise determining a rank order based on the items scores for each of the one or more items in the subset of items, the items of the subset of items being displayed based on the rank order.

8. The system of claim 1, wherein each user-dependent feature includes a feature value that varies between a plurality of users.

9. The system of claim 1, wherein each item-dependent feature includes a feature value that is static between a plurality of users.

10. The system of claim 1, wherein the set of weights of at least one group of the plurality of groups varies based on an activity of one or more users of the social networking service.

11. A non-transitory computer storage media encoded with one or more computer programs, the one or more computer programs comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising:

identifying a set of items that are displayed to a user of a social networking service, one or more items of the set of items comprising digital content distributed using the social networking service and being associated with a plurality of item features, the plurality of item features comprising item-dependent features and user-dependent features;

for one or more items in the set of items, receiving a plurality of feature values, each of the feature values for each item of the one or more items being associated with one of an item-dependent feature and a user-dependent feature;

receiving a plurality of probabilities, each of the probabilities of the plurality of probabilities being associated with a group of a plurality of groups and reflecting a likelihood that the user is a type of user associated with the group, each group of the plurality of groups including a set of weights, wherein each weight of each group is associated with an item feature of the one or more items;

for one or more items in the set of items, determining an item score for the item based on i) for each group, a weighted feature value associated with each item feature of the item for the group and ii) the probability associated with each group, wherein the weighted feature value for each item feature for each group is based on i) the feature value of the item feature and ii) the weight associated with the item feature for the group; and

determining a subset of items to be displayed to the user based on the item scores for each of the one or more items, the subset of items comprising items of the plurality of items.

12. The computer storage media of claim 11, wherein the weighted feature value for each item feature for each group is based on a product of i) the feature value of the item feature and ii) the weight associated with the item feature for the group.

13. The computer storage media of claim 11, wherein the probabilities in the plurality of probabilities vary based on activity of the user within the social networking service.

14. The computer storage media of claim 11, wherein determining the item score comprises selecting a group based on the plurality of probabilities, the item score being determined based on the set of weights associated with the group.

15. The computer storage media of claim 14, wherein selecting a group based on the plurality of probabilities comprises selecting the group having a highest probability.

16. The computer storage media of claim 11, wherein the operations further comprise transmitting instructions to display items in the subset of items to the user.

17. The computer storage media of claim 16, wherein the operations further comprise determining a rank order based on the items scores for each of the one or more items in the subset of items, the items of the subset of items being displayed based on the rank order.

18. The computer storage media of claim 11, wherein each user-dependent feature includes a feature value that varies between a plurality of users.

19. The computer storage media of claim 11, wherein each item-dependent feature includes a feature value that is static between a plurality of users.

20. The computer storage media of claim 11, wherein the set of weights of at least one group of the plurality of groups varies based on an activity of one or more users of the social networking service.

21. A computer-implemented method that is executed using one or more processors, the method comprising:

identifying a set of items that are displayed to a user of a social networking service, one or more items of the set of items comprising digital content distributed using the social networking service and being associated with a plurality of item features, the plurality of item features comprising item-dependent features and user-dependent features;

for one or more items in the set of items, receiving a plurality of feature values, each of the feature values for each item of the one or more items being associated with one of an item-dependent feature and a user-dependent feature;

receiving a plurality of probabilities, each of the probabilities of the plurality of probabilities being associated with a group of a plurality of groups and reflecting a likelihood that the user is a type of user associated with the group, each group of the plurality of groups including a set of weights, wherein each weight of each group is associated with an item feature of the one or more items;

for one or more items in the set of items, determining an item score for the item based on i) for each group, a weighted feature value associated with each item feature of the item for the group and ii) the probability associated with each group, wherein the weighted feature value for each item feature for each group is based on i) the feature value of the item feature and ii) the weight associated with the item feature for the group; and

determining a subset of items to be displayed to the user based on the item scores for each of the one or more items, the subset of items comprising items of the plurality of items.

22. The method of claim 21, wherein the weighted feature value for each item feature for each group is based on a product of i) the feature value of the item feature and ii) the weight associated with the item feature for the group.

23. The method of claim 21, wherein the probabilities in the plurality of probabilities vary based on activity of the user within the social networking service.

24. The method of claim 21, wherein determining the item score comprises selecting a group based on the plurality of probabilities, the item score being determined based on the set of weights associated with the group.

25. The method of claim 24, wherein selecting a group based on the plurality of probabilities comprises selecting the group having a highest probability.

26. The method of claim 21, further comprising transmitting instructions to display items in the subset of items to the user.

27. The method of claim 26, further comprising determining a rank order based on the items scores for each of the one or more items in the subset of items, the items of the subset of items being displayed based on the rank order.

28. The method of claim 21, wherein each user-dependent feature includes a feature value that varies between a plurality of users.

29. The system of claim 21, wherein each item-dependent feature includes a feature value that is static between a plurality of users.

30. The system of claim 21, wherein the set of weights of at least one group of the plurality of groups varies based on an activity of one or more users of the social networking service.