Hi all, I am new to mahout, it has been a couple of days now since I started working with it and I've found it very very powerful.
I noticed, however, a general lack of documentation. I am working just with the recommender system features and, correct me if I am wrong, I can't find anywhere some complete documentation about. All I can find in the official website is some quick-start tutorials. Knowing the theory about recommender systems, I expect a few very simple documentation pages which tell me something like: - The algorithms implemented are: 1) user-based, 2) item-based, 3) .......... - To use 1) in your code, follow these steps: - choose a user similarity measures (available measures: 1) Pearson Correlation 2) Cosine similarity 3) ..... 4).......) - choose a neighbors selection techniques (available techniques 1) threshold 2) fixed number 3).... 4)....) - compute the neighbors using the following UserNeighborhood neighborhood = new ThresholdUserNeighborhood(0.1, similarity, dm);....... and so on until all the options available are covered. I didn't find anything like that, for example at the moment I am trying to figure out how to compute a prediction (user-based algorithm), e.g. predict the rating for user x movie y but I didn't find anything about that. Forgive me if there is something I am missing, I just want to focus on the right content to learn about mahout, any suggestion is welcome. Thanks Regards, Eugenio Tacchini
