Web activities are devided into two type

Alex Iskold at Read/WriteWeb writes about "The Art, Science and Business of Recommendation Engines".
here are two fundamental activities online -- Search and Browse. When a consumer knows exactly what she is looking for, she searches for it. But when she is not looking for anything specific, she browses.

It is the browsing that holds the golden opportunity for a recommendation system, because the user is not focused on finding a specific thing -- she is open to suggestions.

During browsing, the user's attention (and their money) is up for grabs. By showing the user something compelling, a web site maximizes the likelihood of a transaction. So if a web site can increase the chances of giving users good recommendations, it makes more money.

Amazon is considered a leader in online shopping and particularly recommendations. Over the last decade the company has invested a lot of money and brain power into building a set of smart recommendations that tap into your browsing history, past purchases and purchases of other shoppers -- all to make sure that you buy things.

The Amazon system is phenomenal. It is a genius of collaborative shopping and automation that might not be possible to replicate. This system took a decade for Amazon to build and perfect. It relies on a massive database of items and collective behavior that also "remembers" what you've done years and minutes ago.