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I am working on algorithms for collaborative filtering (CF). As part of this work, I want to compare a new algorithm to previous approaches to the problem. I am also surveying the most important methods and publications in publications. So far I have skimmed through around 50 articles, but I have difficulty in pin-pointing the most relevant/interesting.

I want to test my CF-algorithm against a set of other CF-algorithms, both some simple baseline methods and some of the newer methods. Which methods should I compare my algorithm to?

I am going to implement (or find implementations) as many of these as possible during the next couple of months, so it should be possible to get around a fair bit of different methods.

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Rank-boost would be a good benchmark.

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Can you ellaborate on why it would be a good benchmark to use? –  utdiscant Jan 3 '13 at 21:50
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It's a pretty well-known algorithm and not too hard to implement. So if your algorithm can beat that without too much extra effort, it has a certain level of sophistication. I don't think it would be too hard to beat rank-boost. –  user765195 Jan 4 '13 at 1:22

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