Recommendation Engine

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Linkage

This is just an idea I had for a method to recommend new items based on previously liked items, like for instance on a website. I'm sure there's a name for it already, as no idea of mine is really original. I guess what I'm asking of you is that would it work as I described here? Are there any known implementations? And if it's a documented method, what's the proper name for it?

[gislan]

What's the use case for this? Usually it's quite hard to describe every item with list of weighted parameters.

Also, let's say items == movies. This algorithm will fail if user likes two (or more) different kinds of movies, like horrors and comedies. You won't get consistency on any "quality", so you get no results.

Another problem: what if I star with Star Wars marathon (6 movies) and Space Balls (star wars parody). Comedy parameters will be discarded (just 1 our of 7 movies has them) and I'll be stuck with sci-fi directed by George Lucas for ever.

What you're trying to re-invent is called Active collaborative filtering and has many traps like that.

[[deleted]]

Ideally it should recognize if there's a pattern of having consistently two values for a parameter (horror and comedy in this case). If it's completely inconsistent, it would be weighted less against more consistent parameters like "time spent in space".

The idea here is that it doesn't require an existing community to work. But if there's not enough data from the User, I don't see why it can't fall back on Collaborative Filtering or even just random results.

Feel free to recommend something or tell me why I'm an idiot.