Hi Najum,
please write a new mail to ask a question and don't reply to an
unrelated thread --> https://people.apache.org/~hossman/#threadhijack
If you write a new mail, I'm sure we can help you with your recommender
problem. Can you give us a few more details, such as the similarity that
you used, how you did the precomputation and how you exactly measure the
response time?
--sebastian
On 04/17/2014 10:49 AM, Najum Ali wrote:
Hi guys,
I´m pretty much new to mahout and I´m working with this problem here:
I have created a precomputed item-item-similarity collection for a
GenericItemBasedRecommender.
Using the 1M MovieLens data, my item-based recommender is only 40-50% faster
than without precomputation (like 589.5ms instead 1222.9ms).
But the user-based recommender instead is really fast, it´s like 24.2ms? How
can this happen?
Why is item-based so slow?
