Group recommendation based on topic clustering

A system comprising:

• a memory comprising instructions;
• and
• one or more computer processors, wherein the instructions, when executed by the one or more computer processors, cause the system to perform operations comprising:
• clustering posts by associating a topic identifier with each post based on text in the post, the posts having been posted in groups associated with an online service;
• mapping each of the groups to one of the topic identifiers based on topics associated with the posts;
• creating a topic-to-group table mapping each of the topic identifiers to one or more of the groups;
• training a post classifier model with a training set comprising the text of the posts and the topic identifier associated with each post;
• detecting an additional post entered by a user associated with the online service;
• determining, by the post classifier model, a topic identifier for the additional post based on text of the additional post;
• determining a group recommendation for posting the additional post based on the topic identifier for the additional post and the topic-to-group table;
• and
• causing presentation, based on the determining, of the group recommendation to the user for posting the additional post in the recommended group.

A non-transitory machine-readable storage medium including instructions that, when executed by a machine, cause the machine to perform operations comprising:

• clustering posts by associating a topic identifier with each post based on text in the post, the posts having been posted in groups associated with an online service;
• mapping each of the groups to one of the topic identifiers based on topics associated with the posts;
• creating a topic-to-group table mapping each of the topic identifiers to one or more of the groups;
• training a post classifier model with a training set comprising the text of the posts and the topic identifier associated with each post;
• detecting an additional post entered by a user associated with the online service;
• determining, by the post classifier model, a topic identifier for the additional post based on text of the additional post;
• determining a group recommendation for posting the additional post based on the topic identifier for the additional post and the topic-to-group table;
• and
• causing presentation, based on the determining, of the group recommendation to the user for posting the additional post in the recommended group.