R Machine Learning By Example

Issues with recommendation systems

Recommender engines are affected mainly by the following two issues:

• The sparsity problem: Recommender engines work upon user preferences (or ratings for different items, depending upon the application) to predict or recommend products. Usually the ratings are given on some chosen scale but the user may choose not to rate certain items which he/she hasn't bought or looked at. For such cases, the rating is blank or zero. Hence, the ratings matrix R has elements of the form:

  

  For any real world application, such as an e-commerce platform, the size of such a ratings matrix is huge due to the large number of users and ...