Building a recommendation system with an item-based collaborative filtering technique

The recommenderlab package of R offers the item-based collaborative filtering (ITCF) option to build a recommendation system. This is a very straightforward approach that just needs us to call the function and supply it with the necessary parameters. The parameters, in general, will have a lot of influence on the performance of the model; therefore, testing each parameter combination is the key to obtaining the best model for recommendations. The following are the parameters that can be passed to the Recommender function:

  • Data normalization: Normalizing the ratings matrix is a key step in preparing the data for the recommendation engine. The process of ...

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