Yet Another Summer school: The Present and Future of Recommender Systems

September 12-13, 2006 Bilbao, Euskadi

Now I am very exited, I was accepted to a summer school, well, rather a kinda corporate conference, on "The Present and Future of Recommender Systems".

It'll be kick-ass, even Chris Anderson, The Long Tail-guy and John Riedl from the GroupLens will be among speakers!

The event is organised by MyStrands, an online music service, a recommender for music with all the gadgets; using tags, recommending related music, tracking trends, etc. The easy way to input the system is to allow it to hook to your iTunes. They'll check all the music you have there, and recommend something to you that you probably like.

I'm testing it a bit, so now when I turn my iTunes on, it turns the recommender on, and I get some 5 to 10 items that the system thinks I'd like. You can rate them, tag songs, buy them (oh really?!) and also find similar profiles of other users. The site looks good and seems to work pretty well. However, I guess I should really use it more than a few times to know if it really works, and I guess I should at least try and buy a few tunes - just to see whether the match is made in heaven! And, ...just to see whether they can really persuade to me the desired action from their side - to consume.

There's been some interesting usability studies on recommender system by Kirsten Swearingen & Rashmi Sinha a few years back. These were somewhat out of the general strand of the research in the field, as they asked for users' opinions (really!) on the usability issues and most importantly, whether they liked the recommendations. It seems to me, when reading the literature review, that most studies don't even give a hec whether the systems will ever be used by end-users, but they are busy proving the accuracy of algorithms in some bizarre mathematical ways. They come with stuff - genre - yes, this recommender works, it recommends to the user books by her favourite author. Right, just like one didn't know that...

This brings me to think what is it actually that people might want from a recommender system? Do they want it to help them to discover new items that they are not aware of, or just give good secure recommendations on the items that they already feel comfortable with?

Kirsten Swearingen & Rashmi Sinha go for "Different Strokes for Different Folks"-approach on user's needs:

• Reminder recommendations, mostly from within genre (“I was planning to read this anyway, it’s my typical kind of item”)
• More like this” recommendations, from within genre, similar to a particular item (“I am in the mood for a movie similar to GoodFellas”)
• New items, within a particular genre, just released, that they / their friends do not know about
• “Broaden my horizon” recommendations (might be from other genres)
  

From: Beyond Algorithms: An HCI Perspective on Recommender Systems
Kirsten Swearingen & Rashmi Sinha

ps. the pic was done by Adam, Jehad's son. I will have to ask him for cc-licence, so for now it's copyrighted.