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 of the preceding quote for a moment.
- How many times have you come across relevant items to buy, which were suggested by Amazon recommendations?
- How many times have you found your friends when suggested by...
