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Re: How can I build a Collaborative Filtering recommendation framework based on mapreduceMarcos Ortiz 2012-03-31, 16:50
Mahout is built precisely, so I think that you can evaluate it again.
It has to two collaborating filtering algorithms: - Non-distributed recommenders ("Taste") https://cwiki.apache.org/confluence/display/MAHOUT/Recommender+Documentation - Distributed recommenders ("Item-based") https://cwiki.apache.org/confluence/display/MAHOUT/Itembased+Collaborative+Filtering - First-time FAQSs https://cwiki.apache.org/confluence/display/MAHOUT/Recommender+First-Timer+FAQ About the test that you did with Mahout: - Which are the features of your machine? If you are working with 175M of data, a single machine is not the best way to do it. It's more worthy if you use small Hadoop cluster for this (1 NN/JT and 3 DN/TT), and then you can ask on the Mahout mailing list how to improve the performance of your system. Regards On 3/31/2012 6:17 AM, chao yin wrote: > Hi all锟斤拷 > I'm new to mapreduce锟斤拷 but familiar with Collaborative Filtering > recommendation framework. > I tried to use mahout to do this work. But it disappointed me. My > machine work all day to do this job without any result with about 175M data. > Is there anyone knows anything about Collaborative Filtering > recommendation framework based on mapreduce, or mahout, any suggestion > to improve performance锟斤拷 > > -- > Best regards, > Yin -- Marcos Luis Ort锟斤拷z Valmaseda (@marcosluis2186) Data Engineer at UCI http://marcosluis2186.posterous.com 10mo. ANIVERSARIO DE LA CREACION DE LA UNIVERSIDAD DE LAS CIENCIAS INFORMATICAS... CONECTADOS AL FUTURO, CONECTADOS A LA REVOLUCION http://www.uci.cu http://www.facebook.com/universidad.uci http://www.flickr.com/photos/universidad_uci |