I'm working with data very similar to the typical storefront item
scenario. We're trying to find items that a user might like based on
commonalities between them and other users who have bought similar items.
LogLikelihoodSimilarity is working very well for us. However, our
storefront also h
In item-based recommenders, similarity is used as a weight. You can
modify this weight however you like. I think you would find it most
straightforward to modify the recommender to increase the weight when
you are dealing with an item the user "likes", rather than modify the
similarity. You could s
On Wed, Jun 15, 2011 at 9:27 PM, aaron barnes wrote:
> I'm thinking this still most closely resembles a 'boolean' model, because
> it's not a matter of the user assigning a rating to every purchase, so we're
> not looking primarily for users who have given similar ratings to similar
> items, but
Of course, I was making it too complicated. Taking a look at the source
for GenericBooleanPrefItemBasedRecommender made it much clearer. Just
overriding doEstimatePreference worked quite well, and as a bonus, i
don't need to regenerate the ItemSimilarities and get live results when
people lik
