Research user data about beam-recommender HOT 1 OPEN

Interactions could be stored like this:

• user : user fullname
• subreddit : subreddit fullname
• count : sum of all interactions the user has had with the subreddit
• last_interaction : the last time a user has interacted with the subreddit (Unix timestamp)

Now we can give a higher weight to subreddits that users recently interacted with.

There are still problems with this approach. The interactions count will just keep getting higher, but that doesn’t mean that the user recently liked the subreddit. E.g. a user could have visited /r/marvel 30 times last week and one time this week, the total count would be 31, but the user is obviously less interested in Marvel movies this week.

from beam-recommender.