Collective Intelligence in Action

Chapter 12. Building a recommendation engine

This chapter covers

Fundamentals for building a recommendation engine A content-based approach for building a recommendation engine A collaborative-based approach for building a recommendation engine Real-world case studies of Amazon, Google News, and Netflix

In recent years, increasing amount of user interaction has provided applications with a large amount of information that can be converted into intelligence. This interaction may be in the form of rating an item, writing a blog entry, tagging an item, connecting with other users, or sharing items of interest with others. This increased interaction has led to the problem of information overload. What we need is a system that can recommend or present ...