Movie Recommendations System

A Movie Recommendations System is an video recommendations system that implements a movie recommendation algorithm to solve a movie recommendation task.

• Context:
  • It can range from being a Data-Driven Movie Recommendations System to being a Heuristic Movie Recommendations System.
  • It can range from being a Personalized Movie Recommendations System to being a Non-Personalized Movie Recommendations System.
  • ...
• Example(s):
  • Netflix's Movie Recommendation System.
  • Amazon's Movie Recommendation System.
  • …
• Counter-Example(s):
  • a Video Game Recommendation System, such as: PlayStation's Video Game Recommendation System.
  • a Music Recommendation System.
• See: Book Recommendation System.

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References

2016

• http://mapr.com/products/mapr-sandbox-hadoop/tutorials/recommender-tutorial/
  • QUOTE: This tutorial will give step-by-step instructions on how to:
    • Use sample movie ratings data from http://grouplens.org/datasets/movielens/
    • Use a collaborative filtering algorithm from Apache Mahout to build and train a machine learning model
    • Use the search technology from Elasticsearch to simplify deployment of the recommender

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