With good item-item recommendations, there are good heuristic approaches to this. They reduce to a binary and approximate version of Gram-Schmidt orthogonalization.
On Fri, Jun 19, 2009 at 5:04 AM, Sean Owen <[email protected]> wrote: > (And yep, there is an interesting problem to solve here -- automating > that. Building a list of the n *most dissimilar* items on the theory > it's most likely to give the user something recognizable to start > looking at and rating.) > -- Ted Dunning, CTO DeepDyve
