Collaborative Filtering

Collaborative Filtering: Lifeblood of The Social Web – ReadWriteWeb

There are two basic principles involved in Collaborative Filtering.

1. The Wisdom of Crowds and Law of Large Numbers suggest that as communities grow, not only does a large (diverse, independent, etc.) community make better decisions than a handful of editors, but the larger a community gets, the better its decisions will be.  Therefore, we can hypothetically create a Collaboratively Filtered newspaper, television channel, radio station, etc., which would be better (for the community) rather than any other arbitrarily selected medium. In fact, as we will see, services like Digg, YouTube, and Last.fm, are trying to do exactly that – (CF) based media outlets.

2. The second principle of Collaborative Filtering suggests that in any such large community, with enough data on individual participants and on how the individual participants collaborate or correlate with each other, we can make predictions about
what these users will like in the future based on what their tastes have been in the past, i.e. develop a collaboratively filtered recommendation engine. This, of course, relies on the fact that people’s interests, preferences, and ideologies don’t change too drastically over time.

The two aspects of the (CF) system result in two very different and important results.

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