Hands-On Data Science for Marketing

Collaborative filtering

As discussed in the previous section, a collaborative filtering algorithm is used to recommend products based on the history of user behaviors and the similarities between users. The first step to implementing a collaborative filtering algorithm for a product recommendation system is building a user-to-item matrix. A user-to-item matrix comprises individual users in the rows and individual items in the columns. It will be easier to explain with an example. Take a look at the following matrix:

The rows in this matrix represent each user and the columns represent each item. The values in each cell represent whether the ...