How to compute K and n? [Item-based Collaborative Filtering]

I'm currently studying this item-based collaborative filtering algorithm on this thesis that I've researched and I've formulated the algorithm below based on it. I have no problem on steps 1 to 3 but in step 4 it says there: Set the threshold value n.
How can I determine the value of n? Is there a formula for getting the value of it? I already checked it out but there's nothing there.
And also in Step 5: Select the K most similar products in M. The same question, how can I compute the value of K?

1. Retrieve all the item rated by an active user and put it to Q.
2. Isolate the users who have rated both the target item (i) and the items rated by the active user in Q, get the item and put it in R. (co-rated items)
3. Calculate the item similarities using the Pearson Correlation Coefficient with all the items (j) in R.
4. Set the threshold value n, If the similarity of i and j is greater or equal to n, (sim(i,j) >= n), Then include it in M.
5. Select the K most similar products in M.
6. Take the weighted average of the users rating on these similar items K.
• Where in the thesis is that from? Have you tried contacting the author of the thesis for clarification?
– D.W.
Aug 4, 2013 at 22:02
• Actually Sir I've only formulated the algorithm based on my understanding on his thesis. And because the author didn't give his email or number, I've tried to research on the net on his name but unfortunately I can't verify if he is really the person I'm looking for. Aug 6, 2013 at 4:36