But as one commentator recently pointed out even the best recommendation engines suck.

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Most online recommendation engines use collaborative filtering based on purchase or social networks.

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Like other recommendation engines, Baynote attempts to cluster consumers and understand what products or content interest each cluster in real-time.

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One of the biggest problems with history-based recommendation engines, particularly for broad product category e-commerce sites, is that they leverage the wrong signal.

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An unintended consequence of the Netflix challenge though is more knowledge on how we think and act together, as well as more recommendation engines.

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Digital overload is swamping the current recommendation engines, making the sharp knife of human editorial a better filter than the blunt instrument of algorithmic recommendation.

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And as we get better and better at building these expert recommendation engines, we may be able to turn the problem of finding a needle in a haystack, into finding a haystack of needles.

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One area of the Internet that I think is suffering in the current climate of social media, targeted search, and recommendation engines, is the ability for people to find a website on their own.

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If you want a deeper dive into media personalization, recommendation and suggestion engines, check out this panel I did last year.

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