@Dhruv, thank you for sharing this. @Grant, one useful reference is: http://www.ismll.uni-hildesheim.de/pub/pdfs/RendleFreudenthaler2010-FPMC.pdf which I am trying to integrate that into a project.
2011/10/8 Dhruv Kumar <[email protected]> > Here is one reference which I have used earlier for a class project: > > http://jmlr.csail.mit.edu/papers/volume6/shani05a/shani05a.pdf > > One can think of recommendation as an instance of sequential optimal > decision making problem, something which MDPs have been traditionally used > for. > > Given the distributions, solving an MDP boils down to arriving at the > Policy > table enlisting optimal actions to be taken for each state. One can use a > couple of different algorithms--Policy Iteration or Value Iteration to > solve > it. > > If no prior distributions are given, it becomes a more Machine Learning > style of problem. Q-Learning is generally employed in those cases. > > On Sat, Oct 8, 2011 at 6:04 AM, Grant Ingersoll <[email protected]> > wrote: > > > I haven't seen any discussion on it. Do you have a paper or other > > reference on it? That usually helps in discussing how to go about it. > We > > have HMM for classification. > > > > On Oct 7, 2011, at 10:33 PM, Colin wrote: > > > > > I haven't find any MC-based open source recommender. > > > Does Mahout have any plan to provide some? > > > > > > Thank you, > > > -- > > > Colin Wang > > > Skype : colin.bin.wang > > > > -------------------------------------------- > > Grant Ingersoll > > http://www.lucidimagination.com > > Lucene Eurocon 2011: http://www.lucene-eurocon.com > > > > > -- English Name : Colin Wang Skype : colin.bin.wang Chinese Name: Bin Wang QQ: 6807402
