If you're like most people and enjoy listening to The Beatles, here's a recommendation: you might want to check out another British group called Radiohead. Radiohead has been around for two decades, is widely acclaimed within the music industry, and has a very devout following, especially in Britain.

But you may not have heard of Radiohead. Their 1993 alternative rock smash-hit, "Creep", arguably their best-known song, is as melodramatic as they come and very un-Beatles-like. Moreover, Radiohead doesn't play the kind of pop music that made the Beatles famous. Although Radiohead explores a wide variety of sounds, their music can best be described as alternative-rock or punk-rock. Whereas the Beatles took the world by storm, Radiohead took their fame by stealth.

Why then, would a Beatles fan like Radiohead? Well, the proof is in the pudding. The Last.fm pudding, that is. Last.fm is a social music site that aggregates what music its members listen to and tallies the results. It looks to see what artists are played alongside other artists. For example, for all those people who listen to the Beatles, what other artists do they listen to?

The number one match is Bob Dylan, which makes sense since many of the people who grew up with the Beatles also grew up with Dylan. We might expect those two together. However, number two on the list is Radiohead, from a completely different generation and genre of music. According to Last.fm, Beatles fans listen to a lot of Radiohead, and vice versa.

Last.fm Beatles

Recommendation Systems

Last.fm is one of a relatively new breed of web applications called recommendation systems. Recommendation systems aggregate the online behavior of many people to find trends and make recommendations based on them. This involves mathematically calculating how one person's actions relate to another's. But we can think of it as simply finding people who act similarly when listening to music, rating movies, or reading news articles. And the results are sometimes unexpected. For example, who knew Beatles fans might enjoy listening to Radiohead?

In addition to Last.fm, the iTunes music store from Apple has a "Just for You" feature that recommends songs and albums. Amazon.com has long had a recommendations feature, recommending everything from kitchen tools to computers to books. Netflix.com recommends movies and TV shows to watch. Yahoo, IMDB, Rotten Tomatoes, and Metacritic all recommend movies too. These are all straight-forward recommendation systems. In fact, some even tell you so.

Other applications, such as Digg.com, also draw on the same idea of aggregating the actions of many people to present content. Digg and Reddit harness users’ actions to recommend top news stories. The New York Times has a "Most Popular" section that displays the most emailed and most blogged stories. Del.icio.us has a "popular" page that displays the most-saved bookmarks. TripAdvisor recommends lodging and places to visit. Techmeme, a social news site, counts links on blogs as votes to recommend news from the tech industry. Flickr has a photo recommendation feature they call "interestingness." It’s also not too much of a stretch to think of Google as a recommendation system, recommending results based on the search keywords users enter.

The Benefits of Recommendation Systems

The success of applications that recommend is growing. Recommendation systems are no longer a novelty. They're being built for almost every domain where we can give recommendations, and their advantages are clear.


Recommendation systems are not perfect. They have several drawbacks that design teams should consider if they’re thinking about implementing them.

Going Forward

Recommendation systems are popping up everywhere, from movies to news to travel and leisure. They provide valuable, personalized information that can greatly influence the way we use the Web. Like any system, however, they are not without their faults.  But their benefits seem to outweigh their drawbacks, and they might even be the beginnings of an artificial intelligence for each of us, letting us find our next Radiohead. Recommendation systems are out there: watching, and learning. •

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