In 2003, Linden, Smith, and York of Amazon.com published a paper entitled Item-to-Item Collaborative Filtering, which explained how product recommendations at Amazon work. Since then, this class of algorithmg has gone on to dominate the industry standard for recommendations. Every website or app with a sizeable user base, be it Netflix, Amazon, or Facebook, makes use of some form of collaborative filters to suggest items (which may be movies, products, or friends):
As described in the first chapter, collaborative filters try to leverage the power of the community to give reliable, relevant, and sometime, even surprising recommendations. If Alice and Bob largely like the same movies (say The Lion King, Aladdin, and Toy Story) and Alice also likes Finding Nemo, it is extremely likely that Bob, who hasn't watched Finding Nemo, will...
