This chapter discusses how we can use Hadoop for more complex use cases like classifying a dataset and making recommendations.
The following are a few instances of some such scenarios:
Making product recommendations to users either based on similarities between products (for example, if a user liked a book about history, he/she might like another book on the same subject) or on user behavior patterns (for example, if two users are similar, they might like books the other has read)
Clustering a dataset to identify similar entities; for example, identifying users with similar interests
Classifying data into several groups based on historical data
In this recipe, we will apply these and other techniques using MapReduce. For recipes in this chapter, we will use the Amazon product co-purchasing network metadata dataset available at http://snap.stanford.edu/data/amazon-meta.html.
Note
The contents of this chapter are based on Chapter 8, Classifications, Recommendations, and Finding Relationships...