Hi all,
Based on 1M grouplens data, I tried to use user-based recommender and
item-based recommender to give same user the recommendations. But the results
vary so much. There are 4302 items in dataModel. For user 3 or 8, when
returning 500 recommendeditems, there are only 23 items are in common.
In itembased recommender, I use PearsonCorrelationSimilarity.
In userbased recommender, I use NearestNNeighborhood (size 100),
PearsonCorrelationSimilarity.
Should these results be accepted? Or what should I do to improve this situation?
Thank you very much.
-- Young
