I am wondering what algorithm would be clever to use for a tag driven e-commerce enviroment:
Each item has several tags. IE:
Item name: "Metallica - Black Album CD", Tags: "metallica", "black-album", "rock", "music"
Each user has several tags and friends(other users) bound to them. IE:
Username: "testguy", Interests: "python", "rock", "metal", "computer-science" Friends: "testguy2", "testguy3"
I need to generate recommendations to such users by checking their interest tags and generating recommendations in a sophisticated way.
A Hybrid recommendation algorithm can be used as each user has friends.(mixture of collaborative + context based recommendations).
Maybe using user tags, similar users (peers) can be found to generate recommendations.
Maybe directly matching tags between users and items via tags.
Any suggestion is welcome. Any python based library is also welcome as I will be doing this experimental engine on python language.