Our first goal in building our recommender systems is to load the data in R, preprocess it, and convert it into a rating matrix. More precisely, in each case, we will be creating a
realRatingMatrix object, which is the specific data structure that the
recommenderlab package uses to store numerical ratings. We will start with the jester datasets. If we download and unzip the archive from the website, we'll see that the file
jesterfinal151cols.csv contains the ratings. More specifically, each row in this file corresponds to the ratings made by a particular user, and each column corresponds to a particular joke.
The columns are comma-separated and there is no header row. In fact, the format is almost already a rating ...