How Recommendation Engines Quash Diversity

February 25, 2009
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As regular readers here know, I have strong opinions about how recommendation engines should work. So does Daniel Lemire, a regular reader who specifically argues in favor of diversity in recommender systems. Well, this post is for him and all who share his concern.
In “Does Everything Really Sound Like Coldplay?“, Vegard Sandvold explains:

When a lot […]

As regular readers here know, I have strong opinions about how recommendation engines should work. So does Daniel Lemire, a regular reader who specifically argues in favor of diversity in recommender systems. Well, this post is for him and all who share his concern.

In “Does Everything Really Sound Like Coldplay?“, Vegard Sandvold explains:

When a lot of people (who may otherwise have very diverse tastes in music) listen to Coldplay, Coldplay becomes very well connected with a lot of other artists, and also becomes a hub in what is known as a small-world network. Such networks are the basis for social recommendations. Oscar shows that these hubs are indeed the most popular artists, who again gets recommended more often than others. That is why all roads lead to Radiohead.

The cited Oscar is Oscar Celma, who recently defended his PhD thesis on “Music Recommendation and Discovery In The Long Tail”. I’ve only had a chance to skim the abstract, but I’m optimistic that people are giving more thought to the limitations of current recommendation systems. Of course, I’d really like it if they embraced transparency and exploration. But emphasizing diversity is certainly a worthy endeavor.

Or maybe  everything really does sound like Coldplay…

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