Updating personal content streams based on feedback

• US 9,275,001 B1
• Filed: 12/01/2011
• Issued: 03/01/2016
• Est. Priority Date: 12/01/2010
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Liebald, Benjamin, Nandy, Palash, Sampath, Dasarathi, Niu, Ye, Davidson, Jamie, Ilvento, Christina, Hung, Patrick
• Primary Examiner(s): Srivastava, Vivek
• Assistant Examiner(s): Abedin, Normin
• Application Number:
  US13/309,507
• Publication Number:
  US 20160044131A1
• Time in Patent Office: 1,552 Days
• Field of Search: 709/231, 709/230, 809/230
• US Class Current: 1/1
• CPC Class Codes: G06F 15/16 Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs coordinating program control therefor G06F9/52; in regulating and control system G05B
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification
• CPC Class Codes: G06F 16/435 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/635 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/735 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/7867 using information manually generated, e.g. tags, keywords, comments, title and artist information, manually generated time, location and usage information, user ratings
• CPC Class Codes: G06F 3/0482 Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: H04L 65/60 Network streaming of media packets
• CPC Class Codes: H04L 65/80 Responding to QoS

Abstract

A personal content stream comprising a plurality of videos is generated for a user. The user selects topics used in the generation of a personal content stream. The plurality of user selected topics is expanded to include topics related to one or more of the user selected topics. Each of the topics in the expanded plurality of topics includes a topic weight. Videos are selected that are related to one or more of the expanded plurality of topics to generate a plurality of stream videos. Additional videos are selected and added to the plurality of stream videos as the user watches videos. The topic weights are adjusted during video playback based on feedback from the user.

Claims

1. A computer-implemented method for generating a personal content stream of videos for a user, the method comprising:

accessing a profile of the user, the profile having a plurality of topics describing interests of the user;

selecting a first set of stream topics for a first personal content stream and a second set of stream topics for a second personal content stream based upon the plurality of topics in the profile, each of the stream topics associated with a stream topic strength (STS), the STS for each of the stream topics representing a degree of association between the user and the stream topic for a given personal content stream, wherein a stream topic included in both the first set of stream topics and the second set of stream topics is associated with a first STS for the first personal content stream and a second STS for the second personal content stream;

selecting a plurality of videos for inclusion in the first personal content stream and the second personal content stream for the user, each selected video for the first personal content stream associated with one of the stream topics included in the first set of stream topics and selected for inclusion in the first personal content stream based on the STS for the stream topic associated with the selected video, and each selected video for the second personal content stream associated with one of the stream topics included in the second set of stream topics and selected for inclusion in the second personal content stream based on the STS for the steam topic associated with the selected video; and

providing the first personal content stream and the second personal content stream to the user.

2. The computer-implemented method of claim 1, further comprising:

receiving feedback indicating an interaction of the user with a video from at least one of the first personal content stream and second personal content stream provided to the user.

3. The computer-implemented method of claim 2, wherein the interaction is associated with an interaction strength, the interaction strength describing a degree of association of the user and the video.

4. The computer-implemented method of claim 3, wherein the interaction strength is based on implicit feedback from the user.

5. The computer-implemented method of claim 3, wherein the STS of the stream topic of the video is modified according to the interaction strength.

6. The computer-implemented method of claim 5, wherein the stream topic is removed from the first set of stream topics or the second set of stream topics responsive to the STS of the stream topic being below a threshold value.

7. The computer-implemented method of claim 3, wherein the interaction strength of the interaction is based on a frequency of the interaction.

8. The computer-implemented method of claim 3, wherein the interaction strength of the interaction is based on a duration of the interaction.

9. The computer-implemented method of claim 3, wherein the interaction strength of the interaction is based on an amount of time elapsed since an occurrence of the interaction.

10. The computer-implemented method of claim 1, further comprising:

adding a stream topic to at least one of the first set of stream topics or the second set of stream topics based on a strength of co-occurrence of the stream topic with at least one of the stream topics in the first set of stream topics or the second set of stream topics.

11. A computer program product comprising a non-transitory computer-readable storage medium storing program code configured to cause a processor to execute steps comprising:

accessing a profile of the user, the profile having a plurality of topics describing interests of the user;

selecting a first set of stream topics for a first personal content stream and a second set of stream topics for a second personal content stream based upon the plurality of topics in the profile, each of the stream topics associated with a stream topic strength (STS), the STS for each of the stream topics representing a degree of association between the user and the stream topic for a given personal content stream, wherein a stream topic included in both the first set of stream topics and the second set of stream topics is associated with a first STS for the first personal content stream and a second STS for the second personal content stream;

selecting a plurality of videos for inclusion in the first personal content stream and the second personal content stream for the user, each selected video for the first personal content stream associated with one of the stream topics included in the first set of stream topics and selected for inclusion in the first personal content stream based on the STS for the stream topic associated with the selected video, and each selected video for the second personal content stream associated with one of the stream topics included in the second set of stream topics and selected for inclusion in the second personal content stream based on the STS for the steam topic associated with the selected video; and

providing the first personal content stream and the second personal content stream to the user.

12. The computer program product of claim 11, wherein the code is further configured to cause to processor to execute steps comprising:

receiving feedback indicating an interaction of the user with a video from at least one of the first personal content stream and second personal content stream provided to the user.

13. The computer program product of claim 12, wherein the interaction is associated with an interaction strength, the interaction strength describing a degree of association of the user and the video.

14. The computer program product of claim 13, wherein the interaction strength is based on implicit feedback from the user.

15. The computer program product of claim 13, wherein the stream topic is removed from the first set of stream topics or the second set of stream topics responsive to the STS of the stream topic being below a threshold value.

16. The computer program product of claim 13, wherein the STS of the stream topic of the video is modified according to the interaction strength.

17. The computer program product of claim 13, wherein the interaction strength of the interaction is based on a frequency of the interaction.

18. The computer program product of claim 13, wherein the interaction strength of the interaction is based on a duration of the interaction.