Recommending Movies Using Affinity Analysis

In this chapter, we will look at affinity analysis which determines when objects occur frequently together. This is also colloquially called market basket analysis, after one of the common use cases - determining when items are purchased together frequently in a store.

In Chapter 3, Predicting Sports Winners with Decision Trees, we looked at an object as a focus and used features to describe that object. In this chapter, the data has a different form. We have transactions where the objects of interest (movies, in this chapter) are used within those transactions in some way. The aim is to discover when objects occur simultaneously. In a case where we wish to work out when two movies are recommended by the same reviewers, we can use affinity analysis.

The key concepts of this chapter are as follows:

• Affinity analysis for product recommendations
• Feature association mining using the Apriori algorithm
• Recommendation Systems and the inherent challenges 
• Sparse data formats and how to use them