Item to item similarity matrix -based recommender

This process executes the recommendation based on item to item similarity matrix.

The inputs to the process are context defined macros: %{id} defines an item ID for which we would like to obtain recommendation and %{recommender_no} defines the required number of recommendations. The process internally uses an item to item similarity matrix written in pairwise form (id1, id2, similarity).

The process essentially filters out appearances of the required ID in both of the columns of the pairwise score matrix and then limits the output to the first top %{recommender_no} items based on the score (e.g. similarity) written in the matrix.

The output of the process is an example set consisting of two attributes: recommendation and score of the recommendation.