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Chapter 4. Recommending Movies Using Affinity Analysis

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

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 this example, we wish to work out when two movies are recommended by the same reviewers.

The key concepts of this chapter are as follows:

  • Affinity analysis
  • Feature association mining using the Apriori algorithm
  • Movie recommendations
  • Sparse data formats
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