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Apache Mahout Essentials by Jayani Withanawasam

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Chapter 4. Recommendations

In this chapter, we will cover the recommendation techniques used in Apache Mahout. We will discuss the related MapReduce- and Spark-based implementations with respect to a real-world example, with Java code examples as well as command-line executions.

In this chapter, we will cover the following topics:

  • Collaborative versus content-based filtering
  • User-based recommenders
  • Data models
  • Similarity
  • Neighborhoods
  • Recommenders
  • Item-based recommenders with Spark
  • Matrix factorization-based recommenders
    • SVD recommenders
    • ALS-WS
  • Evaluation techniques
  • Recommendation tips and tricks
 

"A lot of times, people don't know what they want until you show it to them."

 
 --Steve Jobs

Before we proceed with the chapter, let's think about the significance ...

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