Wednesday, November 04, 2009

Using only experts for recommendations

A recent paper from SIGIR, "The Wisdom of the Few: A Collaborative Filtering Approach Based on Expert Opinions from the Web" (PDF), has a very useful exploration into the effectiveness of recommendations using only a small pool of trusted experts.

The results suggest that using a small pool of a couple hundred experts, possibly your own experts or experts selected and mined from the web, has quite a bit of value, especially in cases where big data from a large community is unavailable.

A brief excerpt from the paper:
Recommending items to users based on expert opinions .... addresses some of the shortcomings of traditional CF: data sparsity, scalability, noise in user feedback, privacy, and the cold-start problem .... [Our] method's performance is comparable to traditional CF algorithms, even when using an extremely small expert set .... [of] 169 experts.

Our approach requires obtaining a set of ... experts ... [We] crawled the Rotten Tomatoes web site –- which aggregates the opinions of movie critics from various media sources -- to obtain expert ratings of the movies in the Netflix data set.
The authors certainly do not claim that using a small pool of experts is better than traditional collaborative filtering.

What they do say is that using a very small pool of experts works surprisingly well. In particular, I think it suggests a good alternative to content-based methods for bootstrapping a recommender system. If you can create a high quality pool of experts, even a fairly small one, you may have good results starting with that while you work to gather ratings from the broader community.


Xavier Amatriain said...

Thanks for your comment on our research Greg!

If you want more info on this, there is a related post on my blog.

Daniel Lemire said...

Of course, selecting the "experts" is key. I guess that is exactly the process I follow in selecting blogs to read. It is hard work, especially because "experts" come and go and they are context sensitive.

cDima said...

Hi Greg, I'd like to use you as a social filter. Where is your twitter and shared google reader items? :)