I gave this presentation as part of the Big Data Week Conferences in London, 25th April, 2012.
Mendeley Suggest is a research article recommendation system powered by Mahout. This presentation explores how Mahout's distributed recommender works and how well it performs when applied to the problem of recommending research to Mendeley users. Based on experimentation, some tips are provided on how to speed Mahout up by tuning it to the characteristics of the training data set. A new recommendation algorithm is also presented that implements user-based collaborative filtering which complements Mahout's existing item-based collaborative filtering algorithm. The user-based implementation will soon be contributed back to the Mahout community.