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Recommender Systems

  • Laura Igual,
  • Santi Seguí

摘要

In this chapter, we introduce what recommender systems are, how they work and how they can be implemented in Python. We also present the taxonomy of different types of recommender systems based on the information they use, as well as the output they produce. We provide some insights in order to see how recommender systems can deal with questions such as: Which movie should I rent? Which TV should I buy? Or: Which is the best place for me and my family to travel to? These are typical questions that companies like Netflix or Amazon include in their products. We also see and discuss how recommender systems should be evaluated. Finally, a practical case with MovieLens dataset is presented.