Dear Mahout team, Need some advice. The books "Mahout/Hadoop in action" and online information has helped me digest the basic concepts and setup a single node hadoop + mahout (run examples/write test programs/build etc.).
I am prototyping a solution for an analytics problem using User/Itemrecommender structure (to start with). I have a list of 300 thousand users who have bought (on average) 10 items from a finite set of 300 items. I dont have individual preferences for each item bought. As the items are expensive, require pre-buy research and have very low complaint/returns, I am assuming that users liked the items they bought (for first iteration till I get more sophisticated data). Any advice on how best to approach the scenario with item or user based recommendation (given the lack of spread in ratings/preferences)? Appreciate your advice. Manju
