Hi, First of all, a big thanks to Ted and Pat, and all the authors and developers around Mahout.
I'm putting together an eCommerce recommendation framework, and have a couple of questions from using the latest tools in Mahout 1.0. I've seen it hinted by Pat that real-time updates (incremental learning) are made possible with the latest Mahout tools here: http://occamsmachete.com/ml/2014/10/07/creating-a-unified-recommender-with-mahout-and-a-search-engine/ But once I have gone through the first phase of data processing, I'm not clear on the basic direction for maintaining the generated data, e.g with added products and incremental user behaviour data. The only way I can see is to update my input data, then re-run the entire process of generating the similarity matrices using the itemSimilarity and rowSImilarity jobs. Is there a better way? James
