A good way to find differing clumps of opinion based on user ids. Probably also want to consider number of reviews or we may get too many semi-obscure un-ratable videos. I wonder if filtering by some popularity percentile before clustering would solve that problem?
On Sep 6, 2013, at 10:33 AM, Ken Krugler <kkrugler_li...@transpac.com> wrote: > > Any thoughts on these experiments? Especially how to pick examples for the > user in #1 to rate. I'd probably try to cluster in advance, then at run-time randomly pick N (e.g. 10) clusters, and for each cluster randomly pick a video that's close to the centroid. -- Ken -------------------------- Ken Krugler +1 530-210-6378 http://www.scaleunlimited.com custom big data solutions & training Hadoop, Cascading, Cassandra & Solr
