I'd like to expand on this question and answer: http://stackoverflow.com/questions/15707013/utilizing-multiple-weighed-data-models-for-a-mahout-recommender
Besides ParallelALSFactorizationJob and Myrrix, are there any other ways in which you can feed multiple boolean pref data models into a recommender? Is there any way to weight each model? As I understand it, both of these are implementations of ALS-WR, but I'm wondering if there are any other implementations, algorithms, or even tricks using the existing stack of Mahout components that could get me close to what I'm after. _______________________________________________ This message may contain information that is confidential or privileged. If you are not an intended recipient of this message, please delete it and any attachments, and notify the sender that you have received it in error. Unless specifically stated in the message or otherwise indicated, you may not duplicate, redistribute or forward this message or any portion thereof, including any attachments, by any means to any other person, including any retail investor or customer. This message is not a recommendation, advice, offer or solicitation, to buy/sell any product or service, and is not an official confirmation of any transaction. Any opinions presented are solely those of the author and do not necessarily represent those of Barclays. This message is subject to terms available at: www.barclays.com/emaildisclaimer and, if received from Barclays' Sales or Trading desk, the terms available at: www.barclays.com/salesandtradingdisclaimer/. By messaging with Barclays you consent to the foregoing. Barclays Bank PLC is a company registered in England (number 1026167) with its registered office at 1 Churchill Place, London, E14 5HP. This email may relate to or be sent from other members of the Barclays group. _______________________________________________
