Hi, Given the same input data, should the same list of recommended items be returned regardless of whether one uses Item-based or User-based recommendations? I always thought the answer was yes (same "matrix" just flipped differently is how I imagined it), but I recently saw output of some Mahout-based recommender that returned two different lists of recommendations based on whether User-based of Item-based approach was used. Either the code was buggy or I was wrong. :)
And while I'm at it, I assume that using Tanimoto vs. LogLikelihood will yield different recommendations, right? Again, I'm asking because I saw some Mahout-based recommender recently that used Item-based approach and returned identical lists for both Tanimoto and LogLikelihood. Let: UB stand for User-based IB stand for Item-based TC stand for TanimotoCoefficient LL stand for LogLikelihood And: R1 = UB with TC R2 = UB with LL R3 = IT with TC R4 = IT with LL Then: R1 != R2 <== ? R3 != R4 <== ? And: R1 == R3 <== ? R2 == R4 <== ? Thanks, Otis -- We're hiring Mahout+HBase hackers for Data Mining and Analytics http://blog.sematext.com/2011/04/18/hiring-data-mining-analytics-machine-learning-hackers/
