The leaders in the Neflix competition have made great strides since my last post.
Essentially my understanding is that they have done this by modelling thousands of factors on a daily basis. i.e for each person they model (say 2000) factors on an individual and individual day basis. The set of ratings provided for the competition gives enough information so that you can work out that a particular person had a particular preference of a particular strength on a particular day to watch something funny (or given that there are 2000 factors or so) something rather more obscure (maybe watch something in sepia or something). The ratings also enable you to calculate how much a film meets those requirements (again on a particular day - what seemed funny at one time period may not seem funny at another).
By combining the two sets of factors you can then work out how a person will rate a particular movie and improve your score in the competition. This is an undoubtedly impressive feat from a statistical / machine learning viewpoint.
It strikes me that this is also interesting from a psychological viewpoint - do we really believe that people have such nuanced preferences across such a large number of dimensions. I have an open mind about this - apriori I would have thought people would use many fewer factors in arriving at a rating decision - certainly 2000 factors (or even 20) can't all be combined consciously - the subconscious must be heavily involved. Maybe, on the other hand, there are only a few factors that we take into account - but they are different per person and the only way in which they can be explained is by taking a mix of the 2000 or so factors that are modelled.
It strikes me that depending on your view on the above your choice of research direction on the Netflix competition, recommendation systems and indeed psychological processes in general will vary.
I'd welcome views.