Music recommendations from trending queries

1. A method for providing personalized music recommendations to a user, the method comprising:

identifying, by a processing device of a content sharing platform, a plurality of entities relating to popular search queries submitted via one or more search engine platforms, wherein

the content sharing platform enables sharing of music content between users, and

the plurality of entities include musical artists and other entities distinct from the musical artists;

selecting, by the processing device and from the identified plurality of entities, a set of entities that each represents a distinct musical artist relating the popular search queries;

obtaining, by the processing device, a history of online actions of the user on the content sharing platform;

determining, by the processing device, a subset of the selected set of entities based on the obtained history of online actions of the user, wherein each entity in the determined subset of entities is a distinct musical artist that is relevant to the user;

creating and storing on the content sharing platform, by the processing device, the personalized music recommendations for the user, the personalized music recommendations comprising music content associated with each of the determined subset of entities; and

providing, by the processing device, the personalized music recommendations over a network for presentation to the user, wherein at least one of the presented personalized music recommendations is to be selected by the user for consumption.

2. The method of claim 1 , wherein the popular search queries are search queries submitted by at least a threshold number of users via the one or more search engine platforms over a predefined time period, the one or more search engine platforms comprising at least one search engine platform that is external to the content sharing platform.

3. The method of claim 1 , wherein the distinct musical artist comprises one of a singer, a musician, a composer, a music video director, a music video producer, or a band.

4. The method of claim 1 , wherein the online actions of the user comprise one or more of submitting a search query, accessing a media item, or consuming a media item, wherein the consuming the media item comprises watching or listening to the media item.

5. The method of claim 1 , wherein the determining, based on the history of online actions of the user, the subset of the selected set of entities comprises;

identifying musical artists associated with the online actions of the user; and

determining whether any of the identified musical artists matches any of the selected set of entities relating to the popular search queries.

6. The method of claim 1 , wherein the creating the personalized music recommendations for the user comprises:

assigning a score to each of the determined subset of entities based on popularity of respective search queries and relevancy to the user.

7. The method of claim 6 , wherein the creating the personalized music recommendations for the user further comprises:

identifying music recommendation candidates that are ranked based on a plurality of factors; and

improving a rank of any of the identified music recommendation candidates that matches one of the determined subset of entities based on a score assigned to a respective entity of the determined subset of entities.

8. The method of claim 1 , further comprising:

identifying a reference to an artist profile associated with a respective entity in the determined subset of entities; and

providing the reference for presentation to the user together with the personalized music recommendations.

9. The method of claim 1 , further comprising:

identifying an online document indicating why a respective entity in the determined subset of entities is popular; and

providing a reference to the online document for presentation to the user together with the personalized music recommendations.

10. The method of claim 1 , further comprising:

creating a summary indicating why a respective entity in the determined subset of entities is popular; and

providing the summary for presentation to the user together with the personalized music recommendations.

11. The method of claim 1 , wherein the music content of the personalized music recommendations is at least one of a playlist or a channel.

12. A system for providing personalized music recommendations to a user, the system comprising:

a memory; and

a processing device of a content sharing platform, operatively coupled to the memory, the processing device is configured to:

identify a plurality of entities relating to popular search queries submitted via one or more search engine platforms, wherein

the content sharing platform enables sharing of music content between users, and

the plurality of entities include musical artists and other entities distinct from the musical artists;

select, from the identified plurality of entities, a set of entities that each represents a distinct musical artist relating the popular search queries;

obtain a history of online actions of the user on the content sharing platform;

determine a subset of the selected set of entities based on the retrieved history of online actions of the user, wherein each entity in the determined subset of entities is a distinct musical artist that is relevant to the user;

create and store, on the content sharing platform, the personalized music recommendations for the user, the personalized music recommendations comprising music content associated with each of the determined subset of entities;

provide the personalized music recommendations over a network for presentation to the user, wherein at least one of the personalized music recommendations is to be selected by the user for consumption.

13. The system of claim 12 , wherein to create the personalized music recommendations for the user, the processing device is configured to:

assign a score to each of the determined subset of entities based on popularity of respective search queries and relevancy to the user.

14. The system of claim 13 , wherein to create the personalized music recommendations for the user, the processing device is further configured to:

identify music recommendation candidates that are ranked based on a plurality of factors; and

improve a rank of any of the identified music recommendation candidates that matches one of the determined subset of entities based on the corresponding score assigned to a respective entity of the determined subset of entities.