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Recommender Systems and the Long Tail

The introduction of The Long Tail by Chris Anderson is available online! Anderson describes how recommender systems help you ‘navigate’ the long tail. He then lists (context-related, time-related) problems of music recommender systems:

  1. They tend to run out of suggestions pretty quickly as you dig deeper into a niche, where there may be few other people whose taste and preferences can be measured. Plus, many kinds of recommendations tend to be better for one genre than for another—rock recommendations aren’t useful for classical and vice versa. In the old hit-driven model, one size fit all. In this new model, where niches and sub-niches are abundant, there’s a need for specialization.
  2. Even where a service can provide good suggestions and encourage you to explore a genre new to you, the advice often stays the same over time. Come back a month later, after you’ve heard all the recommendations, and they’re probably pretty much as they were. … You’ll need another kind of filter to take you to your next stop on your exploration.

Points worthy of further research ;-)