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To compare the performance
of item-based prediction we also entered
the training ratings set into a collaborative filtering
recommendation engine that employs the Pearson nearest neighbor
algorithm (user-user). For this purpose we implemented a flexible prediction
engine that implements user-based CF algorithms. We
tuned the algorithm to use the best published Pearson nearest neighbor
algorithm and configured it to deliver the highest quality prediction
without concern for performance (i.e., it considered every possible
neighbor to form optimal neighborhoods).
Badrul M. Sarwar