A blog is like a library - filled with hidden treasures. YouWillAlsoLike is a simple yet powerful article recommender system that will help your users to find these treasures. This is an excerpt from the book The Everything Store of what happened when installed a recommender system:

Eric Benson took about two weeks to construct a preliminary version that grouped together customers who had similar purchasing histories and then found books that appealed to the people in each group. That feature, called Similarities, immediately yielded a noticeable uptick in sales and allowed Amazon to point customers toward books that they might not otherwise have found. Greg Linded, and engineer who worked on the project, recalls [Jeff] Bezos coming into his office, getting downed on his hand and knees, and joking, "I'm not worthy."

According to the book Big Data, a third of all of Amazon's sales are said to result from its recommendation and personalization systems. For the online film rental company, Netflix, 75 percent of new orders come from recommendations.


How does it work?
YouWillAlsoLike will mine your blog, find related articles to each article by using data mining methods, and then recommend 5 articles to each article.

Are the results any good?
It's difficult to judge whether a recommended article is good, but we can compare with other recommender systems. According to the image below, the articles recommended by YouWillAlsoLike are more relevant than the recommended articles by LinkWithin, which is another common article recommender system.

Can I test it?
Yes you can! You can see it live here Habrador blog.

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