Media content playback for a group of users

Patent metadata

Field	Value
Publication number	US-12216668-B2
Application number	US-202318329442-A
Country	US
Kind code	B2
Filing date	Jun 5, 2023
Priority date	Oct 24, 2019
Publication date	Feb 4, 2025
Grant date	Feb 4, 2025

Abstract

Methods, systems, and computer programs for generating a playlist of media content items for a group of users. Media content items listened to by the selected users are compared to an average user taste profile to select media content items for playback to the group of users.

First claim

What is claimed is:

1. A method of generating a playlist of media content items for a group of users, the method comprising:
generating a list of candidate media content items selected from at least a media consumption history of a first user and a media consumption history of a second user;
comparing a group taste profile with the candidate media content items in the list of candidate media content items;
ranking the list of candidate media content items based on the comparison; and
generating a playlist selected from the ranked list of candidate media content items, wherein:
the playlist includes contributions of media content items from the first user and the second user; and
the contribution of each user is no more than fifty percent of a total number of media content items in the playlist.

2. The method of claim 1 , wherein the playlist includes a plurality of media content items arranged in a sequence to rotate between contributions from each user.

3. The method of claim 1 , wherein generating the playlist comprises arranging selected media content items into a particular sequence.

4. The method of claim 3 , wherein arranging the selected media content items into the particular sequence comprises ordering the selected media content items according to a minimum separation threshold for media content items by a same artist.

5. The method of claim 3 , wherein the particular sequence comprises, in order, a first media content item of the media consumption history of the first user, one or more media content items with similarity scores compared to the first media content item above a threshold, a second media content item of the media consumption history of the second user, and one or more media content items with similarity scores compared to the second media content item above the threshold.

6. The method of claim 5 , wherein the first media content item has a highest similarity score of the list of the media content items and the second media content item has a next highest similarity score of the list of media content items.

7. The method of claim 1 , further comprising generating the group taste profile based at least in part on individual user taste profiles of the first user and the second user.

8. The method of claim 1 , further comprising:
representing the group taste profile as a group taste profile vector in a multi-dimensional vector space, the dimensions of the multi-dimensional vector space corresponding to characteristics of media content; and
representing media content item vectors for each of the candidate media content items of the list of candidate media content items in the multi-dimensional vector space,
wherein comparing the group taste profile with the candidate media content items in the list of candidate media content items is based at least in part on a distance between the respective media content item vector and the group taste profile vector.

9. The method of claim 8 , wherein ranking the list of candidate media content items is based at least in part on the distance.

10. The method of claim 1 , further comprising:
generating a first user taste profile vector of the first user and a second user taste profile vector of the second user in a multi-dimensional vector space, the dimensions of the multi-dimensional vector space corresponding to characteristics of media content;
generating a group taste profile vector of the group taste profile in the multi-dimensional vector space based on an average of the first user taste profile vector and the second user taste profile vector; and
generating media content item vectors for each of the candidate media content items of the list of candidate media content items in the multi-dimensional vector space,
wherein comparing the group taste profile with the candidate media content items in the list of candidate media content items is based at least in part on a distance between the respective media content item vector and the group taste profile vector.

11. The method of claim 1 , wherein the contributions are uniform.

12. A system comprising non-transitory memory and at least one processing device in data communication with the memory, wherein the memory stores data instructions that, when executed by the at least one processing device, cause the at least one processing device to:
generate a list of candidate media content items selected from at least a media consumption history of a first user and a media consumption history of a second user;
compare a group taste profile with the candidate media content items in the list of candidate media content items;
rank the list of candidate media content items based on the comparison; and
generate a playlist selected from the ranked list of candidate media content items, wherein:
the playlist includes contributions of media content items from the first user and the second user; and
the contribution of each user is no more than fifty percent of a total number of media content items in the playlist.

13. The system of claim 12 , wherein to generate the playlist comprises to arrange selected media content items into a particular sequence.

14. The system of claim 13 , wherein to arrange the selected media content items into the particular sequence comprises to order the selected media content items according to a minimum separation threshold for media content items by a same artist.

15. The system of claim 13 , wherein the particular sequence comprises, in order, a first media content item of the media consumption history of the first user, one or more media content items with similarity scores compared to the first media content item above a threshold, a second media content item of the media consumption history of the second user, and one or more media content items with similarity scores compared to the second media content item above the threshold.

16. The system of claim 15 , wherein the first media content item has a highest similarity score of the list of the media content items and the second media content item has a next highest similarity score of the list of media content items.

17. The system of claim 12 , wherein the instructions further cause the at least one processing device to generate the group taste profile based at least in part on individual user taste profiles of the first user and the second user.

18. The system of claim 12 , wherein the instructions further cause the at least one processing device to:
represent the group taste profile as a group taste profile vector in a multi-dimensional vector space, the dimensions of the multi-dimensional vector space corresponding to characteristics of media content; and
represent media content item vectors for each of the candidate media content items of the list of candidate media content items in the multi-dimensional vector space,
wherein to compare the group taste profile with the candidate media content items in the list of candidate media content items is based at least in part on a distance between the respective media content item vector and the group taste profile vector.

19. The system of claim 12 , wherein the instructions further cause the at least one processing device to:
generate a first user taste profile vector of the first user and a second user taste profile vector of the second user in a multi-dimensional vector space, the dimensions of the multi-dimensional vector space corresponding to characteristics of media content;
generate a group taste profile vector of the group taste profile in the multi-dimensional vector space base

Assignees

• Spotify Ab

Inventors

• Kizelshteyn Mark
• Jansson Andreas
• Churray Tracey
• Koh Mark

Classifications

• G06F16/44

  Browsing; Visualisation therefor · CPC title

• H04N21/26258 Primary

  for generating a list of items to be played back in a given order, e.g. playlist, or scheduling item distribution according to such list (retrieval of multimedia data based on playlists G06F16/40) · CPC title

• H04N21/2668

  Creating a channel for a dedicated end-user group, e.g. insertion of targeted commercials based on end-user profiles {(information retrieval from the Internet by querying with filtering and personalisation G06F16/9535; arrangements for replacing or switching information during the broadcast H04H20/10; push services over packet-switching network H04L12/1859; adaptation of message content in packet-switching networks H04L51/063)} · CPC title

• G06F16/41

  Indexing; Data structures therefor; Storage structures · CPC title

• G06F16/24578 Primary

  using ranking · CPC title