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Item Similarity Computation
One critical step in the itembased collaborative filtering algorithm
is to compute the similarity between items and then to select the most
similar items. The basic idea in similarity computation between two
items i and j is to first isolate the users who have rated both
of these items and then to apply a similarity computation technique
to determine the similarity s_{i,j}. Figure 2 illustrates
this process, here the matrix rows represent users and the columns
represent items.
Figure 2:
Isolation of the corated items and similarity computation

There are a number of different ways to compute the similarity between
items. Here we present three such methods. These are cosinebased
similarity, correlationbased similarity and adjustedcosine similarity.
Badrul M. Sarwar
20010219